Diagnostic apparatus for analyzing arterial pulse waves

ABSTRACT

The present invention relates to a diagnosis apparatus for analyzing arterial pulse waves comprising a database  26  in which is stored data showing the relationship between data representing a pulse wave of a living body and teaching data representing conditions of the living body; and a micro-computer  21  for outputting teaching data corresponding to the pulse wave detected from the living body in the teaching data on the basis of the pulse wave detected from the living body and the stored data inside database  26 . As a result, it becomes possible to perform diagnoses equivalent to a skilled doctor.

This is a divisional of U.S. application Ser. No. 08/302,705, filed Dec.5, 1994, now U.S. Pat. No. 6,261,235 and a continuation ofPCT/JP94/00011, filed Jan. 7, 1994.

BACKGROUND OF THE INVENTION

1. Technical Field

The present invention relates to a diagnostic apparatus for performingdiagnostics based on parameters and data obtained from the pulse wavesgenerated by a living body, and to a pulse wave analyzing apparatus forgenerating the parameters and data representing the pulse waves of theliving body.

2. Background Art

The traditional medicine, for example, the Chinese medicine has longpracticed pulse taking at three locations (Chun, Guan, and Chi) on anarm along the radial artery. Also, there is a method for taking pulsesautomatically with three piezoelectric elements which are respectivelypressed at the three points. (Japanese Patent Application (JPA), SecondPublication, S57-52054). Further, to equalize the finger pressure at thepiezoelectric elements, it is known that air pressure is used to pressdown the piezoelectric elements (JPA, First Publication, H04-9139).

On the other hand, a technique called Ayurveda has been known intraditional Indian medicine from ancient times. This method will beexplained with reference to FIGS. 3A and 3B.

An examiner places his fingers lightly on three locations along theradial artery of an examinee. The three locations shown in FIG. 3A arereferred to as Vata (V), Pitta (P) and Kapha (K), and correspond roughlyto the three locations in the Chinese Medicine known as the Chun, Guanand Chi. The examiner places his second finger on Vata (V), his thirdfinger on Pitta (P) and his fourth finger on Kapha (K), and checks thepulsing motions at the variant depths.

Next, the examiner performs a diagnostic analysis of the healthcondition of the examinee based on the sections and strength of theexaminee's pulse felt at the four points on his one finger asillustrated in FIG. 3B. It follows, therefore, that with the threefingers, he can perform the diagnostic analysis based on a total oftwelve points.

Such wrist pulse method and the Ayurveda technique are said to provideexcellent diagnostics, but because these techniques are dependent on theaccumulated experience and the sensation felt by the Examiner, thetechniques are difficult to be fully mastered. In particular, diagnosisby the Ayurveda method is restricted to those with extreme sensitivityat the finger tip, which can number as little as one in a thousand, orone in several thousand people. Moreover, even for those with sensitivetouch, unless they have had many years of training, they cannot make anaccurate diagnosis.

As described above, the pulse waves are useful index of the conditionsof a living body, and potentially form an excellent basis for adiagnostic technique. If it is possible to derive information related tothe conditions of the living body from the pulse waves, and to performobjective and accurate diagnostics based on such information, it wouldsignify a great leap in the field of remedial medicine.

The present invention was made in view of the background of thediagnostics technology presented above, and some of the objectives ofthe present invention are to present:

(1) A diagnostic apparatus for performing diagnosis of the conditions ofan examinee based on the pulse waves obtained from the examinee in amanner similar to expert medical person.

(2) A pulse wave analysis apparatus for analyzing and acquiring datawhich not only reflect the conditions of the examinee but enableobjective diagnosis to be performed.

(3) A diagnostic apparatus for performing objective diagnosis of theconditions of the examinee based on pulse waves obtained from theexaminee.

SUMMARY OF THE INVENTION

To achieve these objectives, the diagnostic apparatus of the presentinvention comprises: an analysis section for generating waveformparameters from the information, obtained from an examinee, representingthe conditions of the examinee; and a diagnostic section for performingdiagnosis of the conditions of the examinee based on the waveformparameters.

More specifically, the analysis section of the present inventiongenerates the following waveform parameters by analyzing the pulse wavesobtained from the examinee:

(1) values of the elements of an electrical circuit model (lumped fourparameter circuit model) which simulates the arterial system of a livingbody from a proximal section to a distal section;

(2) distortion factors in the waveforms in comparison to referencewaveforms obtained from a plurality of living bodies;

(3) peak points (inflection points) in the waveforms and/or theirgeneration timing; and

(4) a frequency spectrum of sequential pulse wave data.

The diagnostic items which can be analyzed by the apparatus of thepresent invention are illustrated by way of various embodiments, anddisclosed in the claims of the present invention.

Other objects and attainments together with a fuller understanding ofthe invention will become apparent and appreciated by referring to thefollowing description and claims taken in conjunction with theaccompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a diagnosis apparatus according to a firstembodiment of the present invention;

FIG. 2 is a plan view showing the essential parts of a pulse wave sensorused in the embodiment;

FIG. 3A is a diagram illustrating the three pulse taking location on thearm of an examinee in Ayurveda technique;

FIG. 3B is a diagram illustrating the four points on the examiner'sfinger in the Ayurveda technique;

FIG. 4A to FIG. 4C are graphs showing examples of detected pulse waves;

FIG. 5A to FIG. 5C are graphs showing examples of detected pulse waves;

FIG. 6 is a graph showing examples of detected pulse waves;

FIG. 7 is a graph showing examples of detected pulse waves;

FIG. 8 is a graph showing examples of detected pulse waves;

FIG. 9 is a graph showing examples of detected pulse waves;

FIG. 10 is a block diagram to show a pulse wave analysis apparatus tocompute dynamic parameters of the circulatory system based on theconcept of a second embodiment of the present invention;

FIG. 11 is a schematic illustration of using the pulse wave detectiondevice and the stroke volume determination device;

FIG. 12 is a schematic circuit diagram showing a lumped four parametercircuit model to simulate the arterial system of a human body;

FIG. 13 is an illustration of the blood pressure waveforms at the aortaascendens and the blood pressure waveforms in the left ventricle of theheart;

FIG. 14 is an illustration of the electrical signal waveform modelingthe blood pressure waveform at the above aorta ascendens;

FIG. 15 is a flowchart showing the routine for the operation of thesecond embodiment;

FIG. 16 is a flowchart showing the routine for the operation of theembodiment;

FIG. 17 is a flowchart showing the routine for the operation of theembodiment;

FIG. 18 is a flowchart showing the routine for the operation of theembodiment;

FIG. 19 is a flowchart showing the routine for the operation of theembodiment;

FIG. 20 is an example waveform showing the radial arterial waveformobtained by an averaging process;

FIG. 21 is an illustration of the overlap display of a radial arterialwaveform obtained by the averaging process and a radial arterialwaveform obtained by the computation processing;

FIG. 22 is an example of the radial arterial waveform obtained by theaveraging process;

FIG. 23 is an illustration of the other electrical signal waveformmodeling the blood pressure waveform at the above aorta ascendens;

FIG. 24 is a perspective of a pulse wave sensor;

FIG. 25 is a block diagram of the pulse wave detection device;

FIG. 26 is a circuit diagram representing the expansion of the lumpedfour parameter circuit model for the arterial system;

FIG. 27 is a schematic block diagram to show of a diagnostic apparatusbased on the shape of pulse Waveforms, and based on the concept of athird embodiment of the present invention;

FIG. 28 is an illustration to explain a method of pulse waveexamination;

FIG. 29 is a schematic block diagram to show the configuration ofanother diagnostic apparatus;

FIG. 30 is a schematic block diagram to show the configuration of theother diagnostic apparatus;

FIG. 31A is a typical waveform of Ping mai type;

FIG. 31B is a typical waveform of Hua mai type;

FIG. 31C is a typical waveform of Xuan mai type;

FIG. 32 is a bar graph to show the relationship between the distortionfactor d and the three types of pulse waveform;

FIG. 33 is a graph to show the relationship between the distortionfactor d and the proximal section resistance Rc;

FIG. 34 is a graph to show the relationship between the distortionfactor d and the distal section blood flow resistance Rp;

FIG. 35 is a graph to show the relationship between the distortionfactor d and the blood flow momentum L;

FIG. 36 is a graph to show the relationship between the distortionfactor d and the vascular compliance C;

FIG. 37 is a bar graph to show the relationship between the proximalsection blood flow resistance Rc and the three types of waveforms;

FIG. 38 is a bar graph to show the relationship between the distalsection blood flow resistance Rp and the three types of waveforms;

FIG. 39 is a bar graph to show the relationship between the blood flowmomentum L and the three types of waveforms;

FIG. 40 is a bar graph to show the relationship between the compliance Cand the three types of waveforms;

FIG. 41 is a block diagram to show another example of calculating thedistortion factor d;

FIG. 42 is an example of pulse waves used in stress level evaluationaccording to an fourth embodiment of the present invention;

FIG. 43 illustrates a psychosomatic fatigue level diagnosticquestionnaire used in the embodiment;

FIG. 44 is a block diagram showing a construction of a first variationof a stress level evaluation apparatus in accordance with the fourthembodiment of the invention;

FIG. 45 is a block diagram showing a construction of a second variationof a stress level evaluation apparatus;

FIG. 46 is a block diagram showing a structural example of the parametersampling unit (or the waveform sampling memory) of the second variation;

FIG. 47 is a diagram illustrating the stored contents of the peakinformation memory of the variation;

FIG. 48 is a diagram illustrating the radial arterial pulse waveformrecorded in the waveform memory of the variation;

FIG. 49 is a display of stress level evaluated by a third variation of astress level evaluation apparatus;

FIG. 50 is a block diagram showing a structure of a pulse wave analyzingapparatus according to a fifth embodiment of the present invention;

FIG. 51 is a block diagram showing the structure of frequency analyzingunit in the embodiment;

FIG. 52 is a diagram illustrating waveform transfer timing from awaveform sampling memory to a frequency analyzing unit;

FIG. 53 is a timing chart showing an operation inside the waveformsampling memory;

FIG. 54 is a diagram explaining an operation of a high speed playbackunit;

FIG. 55 is a diagram explaining the operation of the high speed playbackunit; and

FIG. 56 is a diagram explaining the operation of the high speedplayback, and a sine wave generator.

DESCRIPTION OF THE PREFERRED EMBODIMENTS BEST MODE FOR CARRYING OUT THEINVENTION

Preferred embodiments of the present invention will be explained withreference to the drawings. All of these embodiments are based on theresults of analysis and diagnosis performed on actual pulse wavesdetected from actual examinees.

To facilitate understanding, the embodiments are presented in separateChapters 1 to 5 so that those skilled in the art may be able toduplicate the embodiments.

In Chapter 1, an expert system is presented to perform diagnosis basedon most easily recognizable waveforms so that the principle of thepresent invention can be understood by those skilled in the art. Toperform such a diagnosis, it is necessary that the waveforms arecorrelated to conditions of an examinee, and additionally thoseparameters must be truly reflective of the conditions of the examinee.

In Chapters 2 and 3, circulatory dynamic parameters are chosen torepresent the parameters representing the conditions of an examinee. Amethod for obtaining such hemodynamic parameters are illustrated with anembodiment, as well as an embodiment for a diagnostic apparatus forperforming diagnosis based on such parameters.

In Chapter 4, an embodiment of a diagnostic apparatus is presented toobtain relevant information related to the condition of an examinee, andto perform diagnosis based on such information. The explanationsprovided include specific steps so that those skilled in the art may beable to construct such diagnostic apparatuses in accordance with thepresent invention. The disclosures of Chapter 4 are helpful to thoseskilled in the art to construct devices other than the psychosomaticstress level analysis apparatus presented in the embodiment.

In Chapter 5, an improved pulse wave analysis apparatus is presented tofurther improve the performance of the apparatuses presented in theforegoing embodiments.

CHAPTER 1 Diagnostic Apparatus

First, a first embodiment of the diagnostic apparatus according to thepresent invention will be explained. This diagnostic apparatus has apre-recorded memory which relates the pulse wave data to the conditionsof a living body, and performs comparative analysis to identify thedetected waveform of an examinee with the stored waveforms in thememory.

Chapter 1 is devoted exclusively to the first embodiment of the presentinvention.

CHAPTER 1-1 Structure of the Embodiment

FIG. 2 shows a plan view of a pulse wave sensor used in the embodiment.

In FIG. 2, numerals 81-84 indicate a set of band shaped strain gageswhich are arranged in parallel in the longitudinal direction on a fingerportion of a rubber glove 5. The thickness of the rubber glove 5 isapproximately 200 μm. Standard gauge type adhesive is used to fixedlyattach the strain gages 81-84 to the rubber glove 5.

The details of the strain gages 81-84 are as follows:

Each of the strain gages 81-84 is a thin gauge with a gauge factor of2.1; resistance of 120 ohms; a width (D) of 2.8 mm; a length (L) of 9.4mm; and a thickness of 15 μm. The overall width M of the strain gages81-84 corresponds to the contact width of the finger of the examinerwhen the finger is gently pressed on an arm of the examinee, and is setat approximately 12 mm. Accordingly, the distances (S) between thegauges 81-84 is approximately 0.27 mm.

The strain gauges 81-84 correspond to the measuring points 1-4 as shownin FIG. 3B, and are used to measure the pulsing motion at the respectiveAyurveda shown in FIG. 3A.

The construction of the diagnostic apparatus using the strain gages81-84 will be explained with reference to FIG. 1.

In the figure, a strain gage 81 and a resistor 12 are connected inseries, with a predetermined DC voltage E applied by a voltage source11. Accordingly, an AC voltage V_(i) corresponding to the resistanceratio, is generated across the ends of the strain gage 81. The numeral13 indicates a DC cut-off filter which removes the DC component of theAC voltage V_(i).

The output signal from the DC cut-off filter 13 is amplified by anamplifier 14, and outputted by way of a low pass filter 15 which has acut-off frequency of 20 Hz. FIG. 2 shows only the circuit correspondingto the strain gage 81. Similar circuits are respectively provided forthe other strain gages 82-84.

Subsequently, the output voltage Vo from the low pass filter 15, isconverted into a digital signal by an A/D converter 20, and thensupplied to a micro-computer 21. The micro-computer 21 comprises a CPU24, a ROM 22, a RAM 23, and a display device DP. It also has a database26 as an external memory. A program specifying the operation of the CPU24, is stored in the ROM 22, while a working area is set in the RAM 23.The numeral 25 indicates an input device comprising a keyboard or thelike, whereby various commands and messages can be input to the CPU 24.The numeral 30 indicates a recorder, which prints out waveform datasupplied from the CPU 24, on a specified sheet.

CHAPTER 1-2 Operation of the Embodiment

There are two operative modes of the first embodiment; the learning modeand the diagnostic mode. The explanations for the operation of the firstembodiment are divided into those two modes.

CHAPTER 1-2-1 Learning Mode

The learning mode is used to store the relationship between theparameters representing the pulse waves (waveform parameters) obtainedfrom the examinee and the data representing the conditions of theexaminee (i.e., diagnosis results).

With the above construction, the examiner wears the rubber glove 5 onone hand, and presses the second finger on the Vata (V), the thirdfinger on the Pitta (P), and the fourth finger on the Kapha (K), of theexaminee.

In this condition, respective voltages V_(i) are outputted from a totalof 12 strain gages, corresponding to the pulsing motion of the examinee.The direct current components of these voltages V_(i) are filtered outin the corresponding DC cut-off filters 13, and are supplied to themicro-computer 21 by way of the respective corresponding amplifiers 14,low pass filters 15, and A/D converters 20. The waveforms supplied inthis way are analyzed in the micro-computer 21, and parametersindicating the characteristics are computed. These parameters are thenstored temporarily in the RAM.

In the present embodiment, the amplitudes of the respective frequencycomponents constituting the pulse waves are used as the characterizingparameters. That is to say, a frequency spectrum analysis by FastFourier Transform is carried out for the respective waveforms (theprogram for the Fast Fourier Transform is pre-stored in ROM 22 or RAM23), and the amplitudes of the various frequencies are used asparameters. Further, as will be explained subsequent to Chapter 2, thepresent invention may utilize various other parameters representing thepulse waves.

The examiner then inputs diagnosis results(as teaching data)corresponding to the computed parameters from the input unit 25. Thediagnosis results in this case are those from the sense of the fingertouch, and those from observation of the waveform displayed on thedisplay device, or both of these. Additionally, a completely differentmethod of diagnosis such as a Western medical opinion may also be used.The input may also include words directly indicating the name of anillness and symptoms can be inputted from the input unit 25. The inputdata may also be corresponding codes.

When the diagnosis results from the examiner are inputted, the CPU 24stores these in the database 26 matched with the parameters storedtemporarily in the RAM 23.

Next, the learning mode will be explained for each actual symptoms of anillness.

(1) Chronic Nasal Inflammation

In this example, the patient was a 28 year-old-male, diagnosed byWestern medical opinion to have chronic nasal inflammation.

The pulse waves measured from the patient were recorded by the recorder30. The results are shown in FIGS. 4A-4C. Here the vertical scale inFIG. 4A is 2 times that in FIGS. 4B and 4C. This is done for convenienceto keep the waveform on the scale. Accordingly, the amplitude of UdanaVata (V) waveform is large compared to the other waveforms. Furthermore,from the observation of the measured results of the Vata (V) in FIG. 4(A), it can be seen that the waveform amplitudes for the first andsecond points are much larger compared to those for the third and fourthpoints.

Meanwhile, the micro-computer 21 performs a frequency spectrum analysisby Fast Fourier Transform on the respective waveforms, and the resultsare stored in the RAM 23 as parameters.

For the pulse wave characteristics shown in FIGS. 4, the Ayurvedatechnique gives a diagnostic opinion of a nasal pharynx disorder. Withthe appearance of such pulse waves there is a statistically highprobability of a disorder in the nose, throat or bronchial tube. Thishas been reported in “Visualization of Quantitative Analysis of thePulse Diagnosis in AYURVEDA: K. Kodama, H. Kasahara, The proceeding ofthe 4th world congress holistic approach—health for all in Bangalore,India 1991”.

From the observation of the output results from the recorder 30, and thewaveform shown on the screen of the display DP, and also from anAyurveda diagnosis by sense of touch, or on the basis of a Westernmedical opinion, the examiner inputs an opinion for the diagnosed result(chronic nasal inflammation), or a code indicating this opinion, fromthe input unit 25 into the diagnostic apparatus.

Subsequently, the CPU 24 matches the diagnosed input result with theparameters temporarily stored in the RAM 23, and stores them both in thedatabase 26.

(2) Liver Disorder Example (i)

In this example the patient was a 28-year-old male with a liver disorder(GTO “42”, GPT “63”).

The examiner's pulse wave measurement results are shown in FIGS. 5A-5C.The scales in these Figs. are the same. From these results it can beseen that the amplitude of the waveforms for the Ranjaka Pitta (P) ofthe third finger are large compared to those for the other fingers. Amagnified view of FIG. 5B is shown in FIG. 6. From FIG. 6 it can be seenthat the amplitude for the second point is greater than that for theother points.

The micro-computer 21 performs a frequency spectrum analysis by FastFourier Transform on the respective waveforms in similar manner to theabove case (1), and the results are stored in the RAM 23 as parameters.

Incidentally, the Ayurveda diagnosis indicated a liver disorder or thestomach/intestine problem.

Here the examiner in a similar manner to the above mentioned case, froman Ayurveda opinion by sense of touch, or on the basis of a Westernmedical opinion, inputs an opinion for the diagnosed result (liverdisorder), or a code indicating this disorder, from the input unit 25into the diagnostic apparatus.

Subsequently, the CPU 24 matches the inputted diagnosis result with theparameters temporarily stored in the RAM 23, and stores them in thedatabase 26.

(3) Liver Disorder Example (ii)

Next example is a diagnosis for a different liver disorder. The patientwas a 24-year-old male with a liver disorder (GTO “36”, GPT “52”).

With this patient also, the amplitude of the waveform in the RanjakaPitta (P) was larger than the amplitude for the other fingers. Thewaveform measurement results for this Pitta (P) are shown in FIG. 7. InFIG. 7 it can be seen that the amplitude for the second point is greaterthan that for the other points. Accordingly, with this liver disorderexample also, similar results to those of the before mentioned liverdisorder example (i) were obtained.

In this case also parameter computations by the computer 24, and inputof the results by the examiner are done in a similar manner to the abovecase. However, since the waveforms of FIG. 5 and FIG. 7 were slightlydifferent, the parameters were slightly different to the case of theliver disorder (i). Even though the diagnostic results are the same,because a certain degree of variation appears in the possible parametervalues, the reliability of the limits can be improved by accumulatingmany clinical examples.

(4) Heart Disorder (i)

In this example, the patient was a 26-year-old male having irregularpulses which appeared several times an hour due to an outer contractingventricle of the heart.

With the waveform measurement results of the patient, the amplitude ofthe waveform for the Sadhaka Pitta (P) of the third finger was largerthan these for the other fingers. The waveform measurement results forthe Sadhaka Pitta (P) are shown in FIG. 8. As is clear from FIG. 8, theamplitude for the third point is greater than those for the otherpoints.

Incidentally, the Ayurveda diagnosis indicated a disorder of the heartfor the above illness example. Accordingly, in this diagnosis examplealso, the diagnosis results from the Ayurveda or from Western medicalopinion were inputted for the parameters calculated by the CPU 24, andboth were matched and stored in the database 26 so that the symptomswith respect to the pulse waves could be learnt.

(5) Heart Disorder (ii)

To confirm the reproducibility of the heart disorder example (i), adiagnosis was made for a different heart disorder example. The patientwas a 38-year-old male having irregular pulses which appeared severaltimes an hour due to an outer contracting ventricle of the heart.

With this patient also, the amplitude of the waveform for the SadhakaPitta (P) of the third finger was larger than those for the otherfingers. The waveform measurement results for the Sadhaka Pitta (P) areshown in FIG. 9. As is clear from FIG. 9, the amplitude for the thirdpoint is greater than those for the other points.

In this case also parameter computations by the computer 24 and input ofthe results by the examiner are made in a similar manner to the abovecases, and matched and stored in the database 26.

CHAPTER 1-2-2 Diagnosis Mode

Next, the diagnostic mode will be explained. The diagnostic modeperforms: detection of pulse waves from an examinee; computation of theparameters representing the pulse waves; and diagnosis by reading outapplicable diagnostic results from the database 26.

The examiner operates the input unit 25 to indicate the diagnosis modefor input to the CPU 24. Then in a similar manner to that for thelearning mode, he puts one hand into the rubber glove 5, and his secondfinger presses the examinee at Vata (V); his third finger at Pitta (P);and his fourth finger at Kappa (K).

As a result, respective voltages V_(i) are output from the strain gagesof the respective fingers, and supplied to the microcomputer 21 by wayof the DC cut-off filter 13, amplifier 14, low pass filter 15 and A/Dconverter 20. The micro-computer 21 then calculates parameters toexpress the characteristics of the supplied waveforms, and temporarilystores these in the RAM 23. The CPU 24 then searches in the database 26,for a parameter equal to the parameter temporarily stored in the RAM 23,or the closest parameter to that parameter, reads the diagnosis resultmatched with that parameter, and displays this on the display device DP.In this case, if there is no equivalent parameter, the diagnosis resultscorresponding to the closest parameter are displayed, then that fact isalso displayed at the same time. Such a message is pre-stored in the ROMas character information, and appropriately displayed.

With the display device DP as described above, diagnosis results (asteaching data) such as chronic nasal inflammation, liver disorder, heartabnormality/disorder are displayed. Accordingly, the examiner can make adiagnosis for that patient based on the displayed results.

Here, the embodiment offers an advantage that if teaching data compiledby expert Ayurveda practitioner had been pre-loaded in the diagnosticmemory provided in the learning mode, even a beginner in the Ayurvedatechnique would be able to perform a diagnosis at the expert level.

CHAPTER 1-3 Variation of the First Embodiment

The first embodiment is not limited to the above diagnostic apparatus.For example, a number of variations such as given below are alsopossible.

Variation (i)

In the first embodiment, the frequency spectrum by FFT were used aswaveform parameters. However, instead of this, each value of theelements of a lumped four parameter circuit model simulating thearterial system may be used. The electrical model will be describedbelow.

Variation (ii)

Waveform spectrum obtained by discrete FFT, or waveform spectrumobtained by the so-called maximum entropy method technique may be usedfor the parameter.

Variation (iii)

In the above embodiment, the radial arterial pulse waves were used.However, it is possible to utilize parameters for brain waves or fingertip pulse waves. Moreover, parameters for the accelerating wave of thefinger tip pulse wave may be utilized. The main point is that thepresent invention is applicable provided there is some wave motion whichreflects the condition of the living body. The living body to bemeasured is not limited to human beings but may be other types ofanimals.

Variation (iv)

In the traditional medicine, Ayurveda for example, a large amount ofdiagnostic data has already been accumulated. Accordingly, if this datacan be used directly and quickly in a clinical manner, then there isease when it is better to adjust the number of measuring points to thoseof the traditional medicine. Hence, it is permissible to have less thanfour strain gages provided there is more than one. For example, it isknown that the traditional medicine of Tibet considers two measurementpoints on one finger. Accordingly, in carrying out the diagnosis basedon this traditional medicine, two gauges would sufficient.

Variation (v)

In the circuit shown in FIG. 1, the pulse wave is detected by directlymeasuring the voltage V_(i) across the terminals of the strain gage 81.However a bridge circuit with the strain gage 81 at one side can beconstructed, and the pulse waves are detected by measuring the voltageacross the opposite corners of the bridge circuit. By constructing abridge circuit with the strain gage and three thin film resistors havingthe same temperature resistance coefficient as the strain gage 81adhered to the rubber glove 5, then a temperature drift due for exampleto the body temperature can be compensated for, and the sensitivity canbe improved.

Variation (vi)

In the circuit shown in FIG. 1, a current is supplied continuously tothe strain gage 81. However the current supply to the strain gage 81 maybe intermittent. That is to say, with the circuit in FIG. 1, since theportion of the frequency component of the voltage Vi detected finally aspulse waves only has frequency components below 20 Hz, therefore evenwith the results sampled at a frequency of 40 Hz, adequate waveformreproduction is possible. Hence the current supplied to the strain gage81 can be intermittent, enabling a reduction in power consumption, whichis beneficial, particularly with portable equipment.

Variation (vii)

In the first embodiment, the parameter inside the database 26 matchingthe calculated parameter in the diagnostic mode is retrieved. Howeverinstead of this, respective threshold values can be set for the upperand lower limits of the respective parameters inside the database 26.When in the diagnosis mode, if the calculated parameters fall withinthis range, they can be considered as the relevant parameters inside thedatabase 26, and that diagnosis result may be outputted. Moreover, withthe data inside the database 26, this is updated when new diagnosisresults are inputted for the same parameter. However, if a parameter ofa close value is newly inputted, the above threshold value can beupdated.

Variation (viii)

In the above embodiment, the pulse wave parameter is calculated, storedand a comparison is made. However, when there is no problem withincreasing the memory capacity or processing time, the waveformsthemselves can be stored and compared.

Variation (ix)

It is also possible to display the therapeutic procedure correspondingto the symptoms of the patient together with or instead of the diagnosisresults. The therapeutic procedure may be outputted as the teaching datain the first embodiment. In the learning mode, diagnosis resultstogether with the therapeutics (or the therapeutics instead of thediagnosis results), can be inputted easily.

In the above, the configuration of the basic diagnostic apparatus hasbeen explained. In the following Chapters 2 through to 5, parametersrepresenting the pulse waves will be explained together with the methodof generating such parameters.

CHAPTER 2 Pulse Wave Analyzer for Computing Parameters of theCirculatory System

In the modern medicine, the most common procedure in the examinationprocess of the cardiovascular system of a human body, is to measure theblood pressure and the heart beat rate. However, to perform moredetailed examination, other circulatory dynamic parameters such as thevascular resistance and compliance must also be examined.

Conventionally, to measure such circulatory dynamic parameters, it isnecessary to determine the pressure waveforms and the blood flow rate atthe aorta ascendens and at an incision site. The measurement methodinvolves either directly by an insertion of a catheter in an artery, orindirectly by ultrasonic measurement.

However, according to the catheter method, there is a problem that alarge invasive equipment is required. The ultrasonic technique canmeasure the blood flow non-invasively, but the technique requires expertoperator, and the apparatus is also large.

To solve these problems, the present inventors therefore devised a pulsewave analysis apparatus based on an electrical simulation circuitry tonon-invasively follow the hemodynamics of a living body with the use ofcirculatory dynamic parameters.

More specifically, the pulse wave analysis apparatus operates by:simulating the arterial system from a proximal section to a distalsection with an electrical circuit (hereinbelow referred to as theelectrical model); entering electrical signals representing the pressurewaveforms at the proximal section into the circuit; iterating the valuesof the elements of the circuit so as to duplicate the actual pressurewaveforms detected from the distal section of the examinee; andoutputting the computed results corresponding to each of the circulatorydynamic parameters.

In this case, it is obvious that the computed parameters may be used asthe waveform parameters in the first embodiment.

In this pulse wave analysis apparatus, the radial arterial pressurewaveforms are used as the waveforms to be analyzed in the distal sectionof the living body, and the aorta ascendens pressure waveforms are usedas the waveforms to be analyzed in the proximal section of the livingbody.

Also in this embodiment, the basic assumption is that the pressurewaveforms at the aorta ascendens are nearly constant and are not muchaffected by the conditions of the living body, and it is mainly theperformance of the arterial system which is affected by the conditionsof the living body. This assumption has been clinically verified by theinventors.

In the following, a pulse wave analysis apparatus according to a secondembodiment will be explained.

CHAPTER 2-1 Structure of the Embodiment

FIG. 10 shows a block diagram of the pulse wave analysis apparatus inaccordance with the second embodiment of the invention.

This embodiment computes the circulatory dynamic function of an examineebased on information obtained from evaluation of the circulatory dynamicparameters of a human body with a non-invasive sensor. The actualdetails of the circulatory dynamic parameters will be explained later.

In FIG. 10, the reference numeral 201 refers to a pulse wave detectionapparatus, 202 is a stroke volume determination device. The pulse wavedetection apparatus 201 determines the radial artery waveform via thepulse wave sensor S1 worn on the examiner's hand (or on the wrist of anexaminee), as shown in FIG. 11, and also determines the blood pressureof the examinee via a cuff belt S2 worn on the upper arm section of theexaminee. The waveform of the radial artery is corrected by the bloodpressure, and the corrected waveform of the radial artery is outputtedas electrical analogue signal.

The analogue signal outputted from the pulse wave detection device 201is inputted into an A/D converter 203, and is converted into digitalsignals for every sampling cycle. Also, the stroke volume determinationdevice 202 is connected to the cuff belt S2, as shown in FIG. 11, anddetermines the volume of blood circulated for one pulsation (beat) viathe cuff belt S2, and outputs the results (digital signals) as thestroke volume per pulsation. This measurement can be provided by theso-called Contraction Surface Area method.

Here, the details of the pulse wave sensor S1 will be explained withreference to FIG. 24.

In this figure, the reference numeral 251 refers to a surgical rubberglove, which is provided with strain gages 252-254 at the finger padside of the first joint of the index, third and fourth fingers. Thestrain gages 252-254 are thin gages, and have a gage factor (170), aresistance (2 k ohm), a width (0.5 mm) and a length (4 mm). Each of thestrain gages 252-254 is fixed on a flexible thin base, and is attachedto the rubber glove 251 with thin the base.

Next, the pulse wave detection device 201 is explained with reference toFIG. 25.

In the figure, the reference numeral 268 refers to a known bloodpressure meter, and measures and outputs the blood pressure valuethrough the cuff belt S2. The numeral 261 is a constant current source,and supplies a constant current to the strain gage 252. The ends of thestrain gage 252 generate a voltage V_(g) to correspond to the degree ofphysical strain. The voltage V_(g) is amplified through a direct current(DC) amplifier 262, and is supplied to the DC cut-off circuit 263 and tothe averaging circuit 265. The output voltage generated by the DCamplifier 262 can be expressed as (V_(o)+V_(d)+ΔV). Here V_(o) is thevoltage generated when the examiner wears the glove 251, V_(d) is thevoltage generated when the examiner's finger is pressed against the armof the examinee. The voltage ΔV is an alternating current (AC) voltagegenerated by the pulse pressure of the examinee.

The DC cut-off circuit 263 eliminates the first two DC components fromthe voltages, V_(o), V_(d) and ΔV, and outputs the AC voltage ΔV, i.e.the pulse wave signal. The pulse wave signal is supplied, after removingthe noise, to the micro-computer 204 via a low pass filter 264 with thecut-off frequency of 20 Hz via the A/D converter 203 (See FIG. 10).

On the other hand, the averaging circuit 265 detects the maximum valueof (V_(o)+V_(d)ΔV), and taking a cycle to be to the period of the nextgeneration of the maximum value of (V_(o)+V_(d)+ΔV), obtains an averagevalue of (V_(o)+V_(d)+ΔV). This operation eliminates the AC componentΔV, and the DC component (V_(o)+V_(d)) is outputted. The referencenumeral 266 is a level memory circuit, and when a switch 266 a ispressed down, memorizes the output voltage value at that time of theaveraging circuit 265, and outputs the voltage at the memorized levelperiodically. The numeral 267 is a decrementor, and subtracts the outputvoltage of the level memory circuit 266 from the output voltage of theaveraging circuit 265, and outputs the decremented value.

In FIG. 25, when the examiner wears the glove 251, the DC amplifier 262output a voltage V_(o). When the switch 266 a is pressed in thiscondition, the voltage V_(o) is memorized in the level memory circuit266. Next, the examiner presses the finger while wearing the glove 251on the arm of the examinee, the averaging circuit 265 generates avoltage (V_(o)+V_(d)), and a voltage V_(d) corresponding to the fingerpressure of the finger is outputted via the decrementor 267. At the sametime, the voltage ΔV corresponding to the pulse wave is outputtedsuccessively through the DC cut-off circuit 263, and the low pass filter264. Further, the examiner can carry out his own examination based onfinger feeling using the strain gages 252-254 disposed on the thinrubber glove 251. The above circuit components 261-267 are provided towork with the strain gages 252, but similar circuit components areprovided for the strain gages 253, 254.

The micro-computer 204 performs the following steps in accordance withthe commands inputted through the keyboard 205.

(1) Reading of the pulse waves by storing the sequenced digital signalof the radial artery pulses obtained through the A/D converter 203 in aninternal waveform memory.

(2) Averaging of the pulses taken at the three locations (Chun, Guan,Chi) and taken into the internal memory, and obtaining a correspondingradial artery pulse waveform.

(3) Taking in of pulsing volume data.

(4) Obtaining an equation to correspond with the above one pulse, andbased on this equation, and calculating each parameter to correspondwith an electrical model of the arterial system of the examinee.

(5) Outputting the parameters obtained by parameter computation ascirculatory dynamic parameter from an output device (not shown; forexample, printer, display device etc.)

The details of these processing steps will be explained under theexplanation section for the operation.

CHAPTER 2-1-1 With Respect to the Electrical Model Utilized in ThisEmbodiment

(1) Lumped Four Parameter Circuit Model

In this embodiment, a four-element lumped circuit shown in FIG. 12 isused for an electrical model simulating the circulatory arterial systemof a human body. The elements of the electrical model are correspondingto four circulatory dynamic parameters:

a blood flow momentum at the proximal section in the arterial system;

a vascular resistance due to blood flow at the proximal section in thearterial system;

a vascular compliance; and

a blood flow resistance at the distal section in the arterial system;which are based on the condition of the circulatory system.

In the following, the relation between the four elements of theelectrical model and the four parameters will be explained.

Inductance L: the blood flow momentum at the proximal section in thearterial system  (dyn.s²/cm⁵)

static electrical capacity C: the compliance at the proximal section inthe arterial system (elasticity)  (cm⁵/dyn)

The compliance refers to the elasticity of the blood vessels to signifytheir softness.

electrical resistance Rc: the vascular resistance due to blood flow atthe proximal section in the arterial system  (dyn.s/cm⁵)

electrical resistance Rp: the vascular resistance due to blood flow atthe distal section in the arterial system  (dyn.s/cm⁵)

The electrical currents i, i_(p), i_(c), flowing in the various sectionsof the electrical model correspond to the blood flow rate (cm³/s) in thecorresponding sections. The general voltages e(t), applied to thevarious sections of the model correspond to the pressure (dyn/cm²) atthe aorta ascendens. The terminal voltage V_(p) of the static electricalcapacity C corresponds to the blood pressure at the radial artery.

(2) Approximate Formulas of Response in the Model

Next, the response of the electrical model will be theoreticallyexplained with reference to FIG. 12. Firstly, the following differentialequation will be formed using the four parameters in the Model shown inFIG. 12,

e(t)=R _(c) i+Ldi/dt+v _(p)  (1).

Here, the current i is: $\begin{matrix}{i = {{i_{c} + i_{p}} = {{C\frac{v_{p}}{t}} + {\frac{v_{p}}{R_{p}}.}}}} & (2)\end{matrix}$

Therefore, the above equation (1) can be expressed as: $\begin{matrix}{{e(t)} = {{{LC}\frac{{\,^{2}\left( v_{p} \right)}}{t_{2}}} + {\left( {{R_{c}C} + \frac{L}{R_{p}}} \right)\frac{v_{p}}{t}} + {\left( {1 + \frac{R_{c}}{R_{p}}} \right){v_{p}.}}}} & (3)\end{matrix}$

t is known that the general solution to a differential equation such asthe above equation (3) is obtained from the sum of a particular solutionsatisfying equation (3) and a transient solution satisfying thefollowing equation: $\begin{matrix}{0 = {{{LC}\frac{{\,^{2}\left( v_{p} \right)}}{t_{2}}} + {\left( {{R_{c}C} + \frac{L}{R_{p}}} \right)\frac{v_{p}}{t}} + {\left( {1 + \frac{R_{c}}{R_{p}}} \right){v_{p}.}}}} & (4)\end{matrix}$

Next, a method of solving the above equation (4) will be explained.Firstly, suppose that an attenuating wave vp is expressed as follows:

V _(p) =Ae ^(st)  (5).

Substituting the above equation (5) in the equation (4), $\begin{matrix}{{\left\{ {{LCs}^{2} + {\left( {R_{c} + \frac{L}{R_{p}}} \right)s} + \left( {1 + \frac{R_{c}}{R_{p}}} \right)} \right\} v_{p}} = 0.} & (6)\end{matrix}$

Here, we solve the above equation (6) for s as follows: $\begin{matrix}{s = {\frac{{- \left( {{R_{c}C} + \frac{L}{R_{p}}} \right)} \pm \sqrt{\left( {{R_{c}C} + \frac{L}{R_{p}}} \right)^{2} - {4{{LC}\left( {1 + \frac{R_{c}}{R_{p}}} \right)}}}}{2{LC}}.}} & (7) \\{If} & \quad \\{{\left( {{R_{c}C} + \frac{L}{R_{p}}} \right)^{2} < {4{{LC}\left( {1 + \frac{R_{c}}{R_{p}}} \right)}}},} & (8)\end{matrix}$

then the value of the root in the equation (7) is negative, and theequation (7) will be expressed as follows: $\begin{matrix}\begin{matrix}{s = \frac{{- \left( {{R_{c}C} + \frac{L}{R_{p}}} \right)} \pm {j\sqrt{{- \left( {{R_{c}C} + \frac{L}{R_{p}}} \right)^{2}} + {4{{LC}\left( {1 + \frac{R_{c}}{R_{p}}} \right)}}}}}{2{LC}}} \\{{= {{- \alpha} \pm {j\quad \omega}}},}\end{matrix} & (9)\end{matrix}$

here, $\begin{matrix}\begin{matrix}{\alpha = \frac{R_{c} + \frac{L}{R_{p}}}{2{LC}}} \\{= \frac{L + {R_{p}R_{c}C}}{2{LCR}_{p}}}\end{matrix} & (10) \\{and} & \quad \\{\omega = \frac{{- \left( {{R_{c}C} + \frac{L}{R_{p}}} \right)^{2}} + {4{{LC}\left( {1 + \frac{R_{c}}{R_{p}}} \right)}}}{2{LC}}} & (11)\end{matrix}$

Next, letting: $\begin{matrix}{{A_{1} = {LC}},} & (12) \\{{A_{2} = \frac{L + {R_{c}R_{p}C}}{R_{p}}},} & (13) \\{and} & \quad \\{{A_{3} = \frac{R_{c} + R_{p}}{R_{p}}},} & (14)\end{matrix}$

each of the above equations (10) and (11) will be expressed as follows:$\begin{matrix}{\alpha = \frac{A_{2}}{2A_{1}}} & (15) \\{and} & \quad \\{\omega = {\sqrt{\frac{A_{3}}{A_{1}} - \alpha^{2}}.}} & (16)\end{matrix}$

Thus, the value s is finally decided, and the solution satisfying theequation (4) can be obtained. In accordance with the above analysis, theequation (5) is utilized as an approximate equation expressing theattenuating and vibrating components, included in the response wave ofthe electrical model.

Next, the blood pressure waves at the aorta ascendens are modeled. FIG.13 shows general pressure waves at the aorta ascendens. Therefore, weapproximate the pressure waves with triangular pulse waves shown in FIG.14. Letting the amplitude and the time be the voltages E_(o) and E_(m)and be the time t_(p) and t_(p1), the pressure waveform e(t) at a time tcan be expressed as follows: $\begin{matrix}{{{c(t)} = {E_{o} + {E_{m}\left( {1 - \frac{t}{t_{p1}}} \right)}}},} & (17)\end{matrix}$

when

0≦t<t_(p1); and

e(t)=E₀  (18)

when

t_(p1)≦t<t_(p):

where

E₀ is the voltage to give minimum blood pressure;

(E₀+E_(m)) is the voltage to give a maximum blood pressure;

t_(p) is the period for one pulsation; and

t_(p1) is the period from the point of rise to the minimum point of theblood pressure at the aorta ascendens.

When the waveform e(t), expressed as the above equation (17) and (18),is inputted to the electrical model shown in FIG. 12, the responsewaveform v_(p)(t) is: $\begin{matrix}{{v_{p}(t)} = {E_{\min} + {B\left( {1 - \frac{t}{t_{b}}} \right)} + {D_{m1}^{- {\alpha 1}}{\sin \left( {{\omega \quad t} + \theta_{1}} \right)}}}} & (19)\end{matrix}$

when

0≦t<t_(p1),

v _(p)(t)=E _(min) +D _(m2) e ^(−α(t−t) ^(_(p1)) ⁾sin {ω(t−t_(p1))+θ₂}  (20)

and when t_(p1)≦t<t_(p).

The third term on the right in the equation (19) and the second term onthe right in the equation (20) designate the attenuating components(corresponding to the equation (5) ), and α and ω are given by the aboveequations (15) and (16).

(3) The Relation between Each Element of the Model and Radial ArterialWaveform

Next, other constants in the equations (19) and (20) except α and ω willbe discussed. Firstly, substituting equations (17) and (19) in the abovedifferential equation (3), the following equation (21) can be obtained.

$\begin{matrix}{{E_{o} + {E_{m}\left( {1 - \frac{t}{t_{p1}}} \right)}} = {{\left( {1 + \frac{R_{c}}{R_{p}}} \right)\left( {E_{\min} + B} \right)} - {\frac{B}{t_{b}}\left( {{R_{c}C} + \frac{L}{R_{p}}} \right)t} + {\left\{ {{{{LC}\left( {\alpha^{2} - \omega^{2}} \right)}D_{m1}} - {\alpha \quad {D_{m1}\left( {{R_{c}C} + \frac{L}{R_{p}}} \right)}} + {D_{m1}\left( {1 + \frac{R_{c}}{R_{p}}} \right)}} \right\} ^{{- \alpha}\quad t}{\sin \left( {{\omega \quad t} + \theta_{1}} \right)}} + {\left\{ {{\omega \quad {D_{m1}\left( {{R_{c}C} + \frac{L}{R_{p}}} \right)}} - {2{{LC}{\alpha\omega}D}_{m1}}} \right\} ^{- {\alpha 1}}{{\cos \left( {{\omega \quad t} + \theta_{1}} \right)}.}}}} & (21)\end{matrix}$

For the equation (21) to be valid, the following conditions arenecessary, $\begin{matrix}\begin{matrix}{{E_{o} + E_{m}} = {\left( {1 + \frac{R_{c}}{R_{p}}} \right)\left( {E_{\min} + B} \right)}} \\{{= {E_{o} + {A_{3}B} - {\frac{B}{t_{p}}A_{2}}}},}\end{matrix} & (22) \\\begin{matrix}{\frac{E_{m}}{t_{p1}} = {\frac{B}{t_{b}}\left( {1 + \frac{R_{c}}{R_{p}}} \right)}} \\{{= \frac{B}{A_{3}t_{b}}},}\end{matrix} & (23) \\{{{{LC}\left( {\alpha^{2} - \omega^{2}} \right)} - {\alpha \left( {{R_{c}C} + \frac{L}{R_{p}}} \right)} + \left( {1 + \frac{R_{c}}{R_{p}}} \right)} = 0} & (24) \\{and} & \quad \\{{{R_{c}C} + \frac{L}{R_{p}}} = {2{{{LC}\alpha}.}}} & (25)\end{matrix}$

Because α and ω are given by the above equations (15) and (16), it isnatural that α and ω satisfy equations (24) and (25).

Secondly, substituting equations (18) and (20) in the above differentialequation (3), the following equation (26) can be obtained:$\begin{matrix}{E_{o} = {{\left( {1 + \frac{R_{c}}{R_{p}}} \right)E_{\min}} + {\left\{ {{{{LC}\left( {\alpha^{2} - \omega^{2}} \right)}D_{m2}} - {\alpha \quad {D_{m2}\left( {{R_{c}C} + \frac{L}{R_{p}}} \right)}}} \right\} ^{- {\alpha {({t - t_{p1}})}}}\sin \left\{ {{\omega \left( {t - t_{p1}} \right)} + \theta_{2}} \right\}} + {\left\{ {{\omega \quad {D_{m2}\left( {{R_{c}C} + \frac{L}{R_{p}}} \right)}} - {2{{LC}{\alpha\omega}D}_{m2}}} \right\} ^{- {\alpha {({t - t_{p1}})}}}\cos {\left\{ {{\omega \left( {t - t_{p1}} \right)} + \theta_{2}} \right\}.}}}} & (26)\end{matrix}$

For the equation (26) to be valid, in addition to the equations (23) and(24), the following equation (27) must be satisfied that:$\begin{matrix}\begin{matrix}{E_{0} = {\left( {1 + \frac{R_{c}}{R_{p}}} \right)E_{\min}}} \\{= {A_{3}{E_{\min}.}}}\end{matrix} & (27)\end{matrix}$

The constants in the equations (19) and (20) will be computed inaccordance with the above equations (22)˜(25) and (27) which define thedifferential equation (3). From equation (27), $\begin{matrix}{E_{\min} = {\frac{E_{0}}{A_{3}}.}} & (28)\end{matrix}$

While, from equation (23), B is expressed as follows: $\begin{matrix}{B = {\frac{E_{m}t_{b}}{A_{3}t_{p1}}.}} & (29)\end{matrix}$

Here, substituting the equation (29) in the equation (22), t_(b) isexpressed as follows: $\begin{matrix}{t_{b} = {\frac{{A_{3}t_{p1}} + A_{2}}{A_{3}}.}} & (30)\end{matrix}$

Next, the remaining constants D_(1m), D_(2m), θ₁ and θ₂ are selected sothat the radial arterial waveform v_(p) can be contiguous at t=0,t_(p1), and t_(p). In other words, the values are selected so as tosatisfy the following conditions (a)˜(d).

(a) the coincidence of v_(p)(t_(p1)) in the equation (19) withv_(p)(t_(p1)) in the equation (20)

(b) the coincidence of v_(p)(t_(p)) in the equation (20) with v_(p)(0)in the equation (19)

(c) the coincidence of the differential coefficient in the equation (19)with one in the equation(20) when t=t_(P)

(d) the coincidence of the differential coefficient it in the equation(19) at t=0 with the differential coefficient in the equation (20) atthe time t=t_(P)

That is, the values of D_(1m) and θ₁ are as follows: $\begin{matrix}{{D_{1m} = \frac{\sqrt{D_{11}^{2} + D_{12}^{2}}}{\omega}},} & (31) \\{{\theta_{1} = {\tan^{- 1}\quad \frac{D_{11}}{D_{12}}}},} & (32)\end{matrix}$

where

D ₁₁=(v₀₁ −B−E _(min))ω  (33)

$\begin{matrix}{D_{12} = {{\left( {v_{01} - B - E_{\min}} \right)\alpha} + \frac{B}{t_{b}} + {\frac{i_{01}}{C}.}}} & (34)\end{matrix}$

Here, v₀₁ is the initial value of v_(p) and i₀₁ is the initial value ofi_(p) when t=0.

Also, the values of D_(2m) and θ₂ are as follows: $\begin{matrix}{D_{2m} = \frac{\sqrt{D_{21}^{2} + D_{22}^{2}}}{\omega}} & (35) \\{{\theta_{2} = {\tan^{- 1}\quad \frac{D_{21}}{D_{22}}}},} & (35)\end{matrix}$

where

D ₂₁=(v ₀₂ −E _(min))ω  (36)

$\begin{matrix}{D_{22} = {{\left( {v_{02} - E_{\min}} \right)\alpha} + {\frac{i_{02}}{C}.}}} & (37)\end{matrix}$

Here, v₀₂ is the initial value of v_(p) and i₀₂ is the initial value ofi_(c) when t=t_(p1). The constants in the equation (19) and (20) arethus obtained.

Thirdly, by back-computing the angular frequency ω in the equation (16),the blood resistance R_(c) at the artery center can be expressed asfollows: $\begin{matrix}{R_{c} = {\frac{L - {2R_{p}\sqrt{{LC}\left( {1 - {\omega^{2}{LC}}} \right)}}}{{CR}_{p}}.}} & (39)\end{matrix}$

The condition necessary to make the resistance R_(c) real and positivethat: $\begin{matrix}{\frac{4R_{p}^{2}C}{1 + \left( {2\quad \omega \quad R_{p}C} \right)^{2}} \leq L \leq {\frac{1}{\omega^{2}C}.}} & (40)\end{matrix}$

Generally, the R_(p) is at a level of about 10³ (dyn.s/cm⁵) and the C isabout 10⁻⁴ (cm⁵/dyn), and because the ω is the angular frequency of thevibration component superimposed on the arterial pulse waves, theangular frequency ω can be considered to be over 10 (rad/s), andtherefore the lower limit value of the equation (40) can be regarded as1/ω²C. For simplification, L can be approximated by: $\begin{matrix}{{L = \frac{1}{\omega^{2}C}},} & (41)\end{matrix}$

then the resistance R_(c) becomes: $\begin{matrix}{R_{c} = {\frac{L}{{CR}_{p}}.}} & (42)\end{matrix}$

Using equations (41) and (42), the attenuation constant α in theequation (15) is expressed as follows: $\begin{matrix}{\alpha = {\frac{1}{{CR}_{p}}.}} & (43)\end{matrix}$

Using the equations (41)˜(43) and either α, ω or one of the fourparameters, for example L, the other parameters Rc, Rp and C areexpressed as follows:

R _(c)=αL  (44)

$\begin{matrix}{{R_{p} = \frac{\omega^{2}L}{\alpha}},} & (45) \\{C = {\frac{1}{\omega^{2}L}.}} & (46)\end{matrix}$

It is clear that the parameters of the model are finally decided by α, ωand L based on the equations (44)˜(46).

Here, α and ω can be obtained by the actual measured waveforms of theradial arterial pulse waves. On the hand, L can be computed from thestroke volume SV per one pulsation (beat).

Next, the process of computing L based on the stroke volume SV will beexplained. Firstly, the average E₀₁ of the pressure wave at the aortaascendens is given by $\begin{matrix}{E_{01} = {\frac{{E_{0}t_{p}} + \frac{E_{m}t_{p1}}{2}}{t_{p}}.}} & (47)\end{matrix}$

On the hand, the Rc, Rp, α, ω and L are related by the followingequation: $\begin{matrix}{{R_{c} + R_{p}} = {{{\alpha \quad L} + \frac{\omega^{2}L}{\alpha}} = {\frac{\left( {\alpha^{2} + \omega^{2}} \right)L}{\alpha}.}}} & (48)\end{matrix}$

Next, the average current through the four parameters model, that is thevalue of the average E₀₁ divided by (Rc+Rp), corresponds to an averagevalue of a blood flow (SV/t_(p)) in the artery caused by the heartpulsing motion. Therefore, $\begin{matrix}{\frac{SV}{t_{p}} = {1333.22 \cdot \frac{\alpha \left( {{E_{0}t_{p}} + \frac{E_{m}t_{p1}}{2}} \right)}{\left( {\alpha^{2} + \omega^{2}} \right){Lt}_{p}}}} & (49)\end{matrix}$

where the (1333.22) is the coefficient for conversion in the pressureunit from (mmHg) to (dyn/cm²).

The given equation (49) is solved for L, then the following can beobtained to compute L from the stroke volume SV. $\begin{matrix}{L = {1333.22 \cdot {\frac{\alpha \left( {{E_{0}t_{p}} + \frac{E_{m}t_{p1}}{2}} \right)}{\left( {\alpha^{2} + \omega^{2}} \right){SV}}.}}} & (50)\end{matrix}$

It is possible to obtain the inductance L by measuring the blood flowrate to determine the value to correspond to the average current:$\frac{1}{t_{p}}\left( {{E_{0}t_{p}} + \frac{E_{m}t_{p1}}{2}} \right)$

in the above equation (49). The known methods of measuring the bloodflow rate are impedance method and Doppler method. The Doppler methodcan be performed by either ultrasound or laser.

(4) Expansion of the Electrical Model

Next, the Model shown in FIG. 12 can be expanded to consider thepressure variations at the locations of Chun, Guan and Chi, then acircuit shown in FIG. 26 is obtained.

In this figure, the pressures at the aorta ascendens, Chi, Guan and Chunare expressed by the general voltages e₀(t), e₁(t), e₂(t) and e₃(t),respectively, and the inductance L₁˜L₃, representing the inertia of theblood, the static electrical capacity C₁˜C₃, representing the vascularcompliance and the resistances R_(C1)˜R_(C3), representing theresistance of the blood vessels are connected between the voltagemeasuring terminals.

Also, the electrical resistance R_(p) in FIG. 12 represents the vascularresistance in further distal blood vessels than the arterial distalblood vessel which are to be measured. Therefore, in the Model presentedin FIG. 26, the electrical resistance shown R_(p) in FIG. 12 correspondsto the combined impedance in the later stages of the circuit. Forexample, in FIG. 26, if the combined impedance to the right side of thesingle dot line A-A′ is equated to the electrical resistance R_(p), themodel in FIG. 26 becomes the same as the Model in FIG. 12.

Therefore, in the Expansion Model shown in FIG. 26, it is possible toobtain the values of the elements of the Expansion Model by the sametechnique employed in the Model in FIG. 12. That is, if the combinedimpedance to the right side of the single dot line A-A′ is equated tothe electrical resistance Rp, according to the method presented above,the parameters R_(C1), L₁ and C₁ are obtained on the basis of thewaveforms of the general voltages e₀(t) and e₁(t), similarly theparameters R_(C2), L₂ and C₂ are obtained on the basis of the waveformsof the general voltages e₁(t) and e₂(t), and similarly the parametersR_(C3), L₃, C₁ and Rp₃ are obtained on the basis of the waveforms of thegeneral voltages e₂(t) and e₃(t).

In the above explanation, the waveforms corresponding to the generalvoltages e₁(t)˜e₃(t) are assumed to represent the at-source bloodpressure directly. However, in practice, the waveforms, generated in theblood vessels of the examinee, are changed while being propagatedthrough the muscles, fat tissues and skin of the examinee before beingdetect by the strain gages 252˜254.

Therefore, in order to carry out more detailed analysis, it is necessaryto consider the pressure waveforms. It is suggested that, in such acase, it would be suitable to provide a pressure waveform transformationcircuits 270˜272 as shown in FIG. 26. In the circuit 270, the numeral273 represents a voltage follower circuit; 274, 275 are electricalresistances, 276 is a condenser. The electrical resistances 274, 275simulate the blood pressure drop between the strain gage 254 and thelocation to correspond to the Chi of the artery of the examinee. Theelectrical resistance 275 and the condenser 276 simulate the frequencyresponse, i.e. the decay in the high frequency waveforms. The voltagefollower circuit 273 is provided before the electrical resistance 274because it is considered that the effects of the muscle, fat tissues andskin on the artery itself is slight.

In this model, the voltage e₁(t) is transformed by the pressure waveformtransformation circuit 270 and is detected as e₁′(t). Therefore, toobtain the correct waveform of the voltage e₁, it is necessary to obtainthe constants for each element in the pressure waveform transformationcircuit 270. This is possible by applying sound signals of variousfrequencies and waveforms to the examenee's arm, and analyzing theattenuation and changes in such sound signals. That is, because theconfiguration of the circuit of the pressure waveform transformationcircuit 270 is the same as the Model shown in FIG. 12, the same methodcan be used. Here, it should be noted that the values in the circuit 270are not fixed, and change in accordance with the finger pressures of theexaminer; therefore, it is preferable to record the results of applyingvarious sound signals under various finger pressure on the examinee'sarm, so as to relate the constants to the various pressing pressures.

The above descriptions provided an explanation of the relationship amongthe radial arterial waveforms, stroke volume and each of the elements inthe electrical Model. The microcomputer 204 (See FIG. 10) in thisembodiment computes the values of the parameters in the model inaccordance with the relationship presented in the foregoing.

CHAPTER 2-2 Operation of the Apparatus

FIGS. 15 to 19 show flowcharts for the operation of the waveformanalysis apparatus. FIG. 20 shows the waveforms of the radial arteryobtained by the averaging process, FIG. 21 shows the comparison betweenthe radial artery waveforms W1 obtained by the averaging process and theradial artery waveforms W2 obtained by the parameter computation. Thefollowing explanations are provided with reference to these figures.

CHAPTER 2-2-1 Ordinary Computation Procedure

(1) Reading of Pulse Wave Data

The computation of the circulatory dynamic parameters is performed by:attaching the cuff belt S2 to the examinee as shown in FIG. 11;attaching the pulse wave sensor S1 to the hand of the examiner; pressingdown the switch 266 a (see FIG. 25); and inputting various commandsthrough the keyboard 205. In response to these commands, themicrocomputer 204 sends a command to begin measurements of the pulsewaves to the pulse wave detection apparatus 201. The pulse wavedetection apparatus 201 receives the radial artery pulse wave signalsthrough the strain gages 252˜254, and the sequential digital signalsexpressing the radial pulse waves are outputted from the A/D converter203, and the microcomputer 204 takes in the readings for a set period oftime (about one minute). Thus the microcomputer 204 accumulatessequential digital signals of the plurality of waveforms of thepulsation's.

(2) Averaging Process

Next, the microcomputer 204 computes an average waveform during theone-minute-period based on the plurality of waveforms of the radialartery, and stores this waveform as the representative waveform of theradial artery in the internal memory (step S1). At the same time,averaging is performed on the finger pressures detected via thedecrementor 267 (see FIG. 25). A representative waveform W1 of theradial artery stored in the memory is shown in FIG. 20.

(3) Stroke Volume Computation

When the above averaging process is completed, the microcomputer 204sends out a command to activate the stroke pulsing volume determinationdevice 202. The results of the measurement data per pulsation isforwarded to the microcomputer 204 (step S2).

(4) Parameter Computation Process

Next, the processing by the microcomputer 204 proceeds to step S3, andperforms the parameter computation routine whose flowcharts are shown inFIGS. 16 and 17. With the execution of this routine, the routine ofcomputing α and ω (steps S109 and S117) shown in FIG. 18, is executedfor each of the Chun, Guan and Chi locations. With the execution ofthese α and ω computing routines, the ω computing routine is performed(step S203). To simplify the explanation, it is assumed that thepressure waveforms corresponding to the electrical voltages e₁(t)˜e₃(t)in FIG. 26 are obtained directly from the strain gages 252˜254.

The following is an explanation of the routines described above.

First, the microcomputer 204 examines the radial artery waveforms perpulse in the memory, and determines the first point P₁ in terms of thetime t₁ and blood pressure level y₁ corresponding to the maximum bloodpressure; the second point P₂ in terms of the time t₂ and blood pressurelevel y₂ corresponding to the temporary drop in the blood pressure; andthe third point P₃ in terms of the time t₃ and blood pressure y₃corresponding to the next rise in the blood pressure. Also, themicrocomputer 204 determines the time duration t_(P), the minimum bloodpressure value E_(min) (which corresponds to the 1st term of each of theequations (3) and (4)) with respect to one pulsation of the radialarterial waveforms in the memory (step S101). The above processingproduces the following data, for example, necessary for the parameterscomputation.

First Point: t₁ = 0.104 s, y₁ = 123.4 mmHg Second Point: t₂ = 0.264 s,y₂ = 93.8 mmHg Third Point: t₃ = 0.380 s, y₃ = 103.1 mmHg Pulseduration: t_(p) = 0.784 s Min. Press: E_(min) = 87.7 mmHg Stroke vol.:SV = 103.19 cc/beat

In this case, when the pulse waveform is such that it is difficult todistinguish the second point P₂ from the third point P₃, then the timesfor the point P₂ and P₃ are chosen as

t₂=2t₁,

t₃=3t₁,

and the blood pressure value is determined at these points.

To simplify the calculations, using the value of the blood pressure y₀at the point A shown in FIG. 22, y₁ to y₃ are normalized in steps S102,103, and the initial value of B is determined as:$\frac{y_{0}}{2} - 0.1$

in step S104.

Next, the optimum values of the B, t_(b), α and ω are obtained by thefollowing steps.

(a) First, B is varied between y₀/2 to y₀, and simultaneously is variedbetween t_(p)/2 to t_(p) at an interval of +0.1, and the values of B,t_(b), α and ω are determined so as to minimize V_(p)(t₁)−y₁,V_(p)(t₂)−y₂ and v_(p)(t₃)−y₃.

(b) For the values of B, tb, α and ω the values of B, t_(b), α and ω aredetermined so as to minimize the values of V_(p)(t₁)−y₁, v_(p)(t₂)−y₂and v_(p)(t₃)−y₃.

(c) Based on the values of the B and tb, repeat the steps (a) and (b)within the range of B

B±0.05, t_(b)±0.05

(d) In the above process (a), (b) and (c), the value of α is varied inincrements of 0.1 between 3 to 10 to calculate the optimum values of ωfor each α. The values of ω for α are determined so as to make$\frac{{v_{p}\left( t_{2} \right)}}{t} = 0$

by the binary method (refer to FIG. 10). Furthermore, the values ofv_(P) are calculated with the initial value of v₀₁=0.

According to the above procedure, the following example values aredetermined.

α=4.2 (s⁻¹);

B=27.2 (mmHg);

ω=24.325 (rad/s);

t_(b)=0.602 (s)

(e) Next, the values of tp₁, E_(m) and E₀ are calculated from theequations (28)˜(30), and (44)˜(46) in steps S123, S124. The results ofthis example is shown below.

t_(p1)=0.588 (s)

E_(m)=46.5 mmHg

E₀=90.3 mmHg

(f) Next, using the equation (50), the value of L from the pulsingvolume rate in step S125, and the remaining parameters are obtained fromthe equations (44)˜(46) in step S126. The following examples values areobtained. $\begin{matrix}{L = 7.021} & \left( {{dyn} \cdot {s^{2}/{cm}^{5}}} \right) \\{C = {2.407 \times 10^{- 4}}} & \left( {{cm}^{5}/{dyn}} \right) \\{R_{c} = 29.5} & \left( {{dyn} \cdot {s/{cm}^{5}}} \right) \\{R_{p} = 989.2} & \left( {{dyn} \cdot {s/{cm}^{5}}} \right)\end{matrix}$

Also, total direct current resistance (averaging) value TPR (TotalPeripheral Resistance) is obtained by the following equation.

TPR=R _(c) +R _(p)=1018.7  (dyn.s/cm⁵)

(5) Output Processing

When the above discussed parameter processing is completed, themicrocomputer 204 outputs the values of L, C, R_(c) and R_(p) from theoutput device in step S4. That is, for each waveform from the Chun,Guan, Chi sections, the above computation processes are performed, andthe values of the parameters Li to L₃, C₁ to C₃, R_(C1) to R_(C3) shownin FIG. 26 are obtained.

For confirmation, the parameter values computed are put in equation(40), then

6.696≦L≦7.021

is obtained, and the approximation by equation (41) appears to beproper. Also, as shown in FIG. 21, the radial arterial waveformscalculated from the parameter values are quite similar to those actuallyobserved by averaging over one minute period.

CHAPTER 2-2-2 Continuous Computation

The embodiment according to this invention is provided with a timer, andit is possible to measure the circulatory dynamic parameterscontinuously over a prolonged period of time. To perform continuousmeasurements, the examiner inputs a command for continuous measurementthrough the keyboard 205. When the resulting step S4 (output process)shown in FIG. 15 is completed, the timer is set, and after a set timehas elapsed, the steps from S1 are re-executed, the parameters arecomputed in step S3, and the results are recorded in a recording mediumin step S4. By repeating this process, the continuous computations ofthe parameters are performed.

The examiner may alter the finger pressure suitably after each elapsingof a set time period. That is, in a general pulse examination, theexaminer alters his finger pressure suitably to obtain information onvarious items, therefore the present embodiment may also be used inconjunction with such an examination procedure. By so doing, it becomespossible to obtain various data in accordance with the varying fingerpressures.

CHAPTER 2-3 Variations of the Second Embodiment

In addition to the second embodiment presented above, the followingvariations may be practiced.

Variation (i)

The circulatory dynamic parameters for the radial artery may be obtainedwithout measuring the stroke volume, and assuming the value of L. Tosupplement lowering of the computational accuracy, the embodiment may beconfigured so as to have an overlap display of the computed and measuredradial artery waveforms as shown in FIG. 21, and to have the examinerenter various values of L. In such an embodiment, the examiner performstrial and error process of optimizing the value of L to obtain matchingof the two waveforms.

Variation (ii)

As a model of the radial artery waveform, a waveform shown in FIG. 23, astep-and-ramp waveform may be chosen instead of a triangular waveform.This form is closer to the true waveform than the triangular waveform,and more accurate representation for the circulatory dynamic parametersis obtainable.

Variation (iii)

In the above embodiment, the dynamic parameters were obtained by meansof equations and computations, the waveforms may be simulated by varyingthe parameters within ranges by a simulation circuitry, and theparameters which represent the measured waveforms most accurately may beoutputted. In this case, more complex electrical models for the arterialsystem and for the pressure waveforms for the aorta ascendens may bechosen to obtain more accurate representation of the actual performance,and the measurement accuracy can be improved.

Variation (iv)

The measurement locations for the radial artery and the stroke volumeare not limited to those shown in FIG. 11. For example, by providingblood pressure sensor on the rubber glove 251, both the radial arterialwaveforms and the stroke volume may be determined simultaneously. Inthis case, the examinee does not need to roll up the sleeves, and it ismore convenient, in some cases.

Similarly, the stroke volume determination device may be made on arm,hand or finger on the arm opposite to the pulse taking arm.

Variation (v)

In the above embodiment, to simplify the explanation, the waveformscorresponding to the voltages e₁˜e₃ were assumed to be obtained directlyfrom the strain gages 252˜254, but it is permissible to examine using amodel that incorporates the model for the pressure waveformtransformation circuits 270˜272.

CHAPTER 3 A Diagnostic Apparatus Based on Distortions in the PulseWaveforms

Next, a diagnostic apparatus according to a third embodiment of thepresent invention will be explained. This apparatus first determines thedistortions of the detected pulse waveforms obtained from an examinee.

The distortion in the waveforms refers to deviations from the “normal”pulse waveform shape of a living body, and the waveform shape isobviously closely related to the conditions of the living body, andtherefore, computations of distortions in the waveforms serve as anexcellent guide to diagnostics.

As will be described later in this Chapter, the waveform distortions arealso related to the circulatory dynamic parameters described in Chapter2, and therefore, computations of the waveform distortions will alsoserve as indicators for circulatory dynamic parameters, and will enablediagnosis to be performed based on computed distortions.

In this Chapter, the relationship between waveform distortions andwaveform types/circulatory dynamic properties will be explained first,followed by the presentation of a diagnostic apparatus of a thirdembodiment which utilizes this relationship, and a variation of thethird embodiment.

CHAPTER 3-0 Relationship Between Distortion, Pulse Waveform Shape andDynamic Parameters

Before explaining the operations of the pulse wave diagnostic apparatusof this invention, the relationship between the waveform distortion, thepulse waveform shape and circulatory dynamic parameters will beexplained with reference to the drawings provided on the basis of theinventors experience.

In the following embodiment, the distortion factor d is defined asfollows:$d = \frac{\sqrt{{Q_{2}}^{2} + {Q_{3}}^{2} + \ldots + {Q_{n}}^{2}}}{Q_{1}}$

where

Q₁ is the amplitude of the fundamental wave;

Q₂ is the amplitude of the 2nd harmonics; and

Q_(n) is the amplitude of the nth harmonics

in the Fourier analysis of the pulse waves.

CHAPTER 3-0-1 Relationship Between Waveform Distortion and WaveformShape

First, the relationship between the waveform distortion and waveformshapes of the pulse waves will be explained.

From a variety of shapes of pulse waveforms, those defined as Ping maitype, Hua mai type and Xuan mai type waveforms are typically illustratedin FIGS. 31A, 31B and 31C, respectively. The graphs show blood pressureBP in mmHg plotted on the vertical axis and the time in seconds plottedon the horizontal axis.

The Ping mai is typical shape of a healthy adult, and the waveform shownin FIG. 31A is from a 34-year-old male. The Ping mai type waveform ischaracterized by a gentle double peak waveform having a regular rhythm,and is free of irregularities.

The Hua mai is caused by hemodynamic irregularities, and is symptomaticof an illness causing rapid pulsations of the heart. A typical exampleshown in FIG. 31B is from a 28-year-old male patient. The Hua mai typewaveform is characterized by a rapid rise and fall in the bloodpressure, and by the steeply rising and falling second peak.

The Xuan mai is caused by vascular hardening and is symptomatic of anillness including liver and kidney ailments. This waveform is associatedwith tensions in the autonomic nerve system to cause the walls of theblood vessels to stiffen, and the blood pulsations cannot be properlyreflected in the pulse waveform. A typical example is shown in FIG. 31Cwhich is taken from a 34-year-old male patient. The Xuan mai typewaveform is characterized by a rapid rise followed by a gradual drop inthe blood pressure over a period of time.

FIG. 32 is a bar graph showing the variations of the distortion factor din Hua mai, Ping mai and Xuan mai waveform shapes, and shows theanalytic results of many examinations (21 cases of Hua mai, 35 cases ofPing mai, 22 cases of Xuan mai).

It is shown that in the Ping mai type the pulsing pressure is centeredaround a distortion factor d at 0.907 with a deviation of ±0.05; in theHua mai type, the distortion factor d is larger than the one of the Pingmai type at 1.013 with a deviation of ±0.148; in the Xuan mai type, thedistortion factor d is the smallest of the three types, and is centeredaround 0.734 with a deviation of ±0.064.

The statistical significance of the distortion factors of the waveformtypes was analyzed by t-test, and it was found that the differences inthe waveform shapes were statistically significant with uncertainty ofless than 0.05.

CHAPTER 3-0-2 Relationship Between Waveform Distortion and CirculatoryParameters

Second, the relationship between the waveform distortion and thecirculatory dynamic parameters described in Chapter 2-1-1 will beexplained.

The relationships of the distortion factor d to the circulatory dynamicparameters are shown in FIG. 33 to 36. These data were taken from aexperiment of 120 cases. FIG. 33 shows the relationship of thedistortion factor d to the proximal vascular resistance R_(c), which isexpressed mathematically as:

R _(c)=58.68·d ^(−0.394)

where the correlation coefficient r=−0.807

FIG. 34 shows the relationship between the distortion factor d and thedistal vascular resistance R_(p) which is expressed as:

R _(p)=2321·e ^(−0.615d)

where the correlation coefficient r=−0.418

FIG. 35 shows the relationship between the distortion factor d′ and themomentum L, which is expressed as:

L=162.8·e ^(−2585d)

where the correlation coefficient r=−0.774

FIG. 36 shows the relationship of the distortion factor d to thecompliance C, which is expressed as:

C=10⁻⁴(−1.607+3.342·d)

where the correlation coefficient r=0.764.

CHAPTER 3-0-3 Relationship Between Circulatory Parameters and WaveformShape

Just for, the relationship between the circulatory parameters andwaveform shape will be explained.

FIGS. 37 to 40 are bar graphs showing the four circulatory dynamicparameters for the three waveform types: Hua mai, Ping mai and Xuan mai.FIG. 37 shows the proximal resistance R_(c) for the three waveformtypes. The resistance is the smallest in the Hua mai type at47.048±18.170 (dyn.s/cm⁵). The next smallest is the resistance in thePing Mai type at 92.037±36.494 (dyn.s/cm⁵). The largest resistance isexhibited in the Xuan mai type at 226.093±61.135 (dyn.s/cm⁵).

FIG. 38 shows the distal section resistance R_(p) for the three waveformtypes. In this case, the Hua mai type exhibits the smallest resistanceat 1182.1±176.7 (dyn.s/cm⁵); followed by the Ping mai type at1386.5±228.3 (dyn.s/cm⁵); and the Xuan type mai type exhibits thelargest resistance at 1583.0±251.0 (dyn.s/cm⁵).

FIG. 39 shows the momentum L of the blood flow for the three waveformtypes. The momentum is the smallest in the Hua mai type at 10.337±2.609(dyn.s²/cm⁵); followed by that in the Ping may type at 16.414±4.604(dyn.s²/cm⁵); and the largest L is in the Xuan mai type at 27.550±5.393(dyn.s²/cm⁵).

FIG. 40 shows the compliance C for the three waveform types. The largestcompliance is exhibited by the Ping mai type at (2.030±0.554)·10⁴(cm⁵/dyn); followed by the Ping mai type at (1.387±0.311)·10⁻⁴(cm⁵/dyn); and the Xuan mai type has the smallest compliance at(0.894±0.207)·10⁻⁴ (cm⁵/dyn). The compliance C values for the threetypes of waveforms seem to be opposite to the other parameters, but theorder of the parameters becomes the same for all the waveform shapes,when inverse values, 1/C, of the compliance values are used. Therelationship between the dynamic parameters and the three waveform typeswere subjected to the T-test, and the results were statisticallysignificant with uncertainty of less than 0.05.

CHAPTER 3-1 Diagnostic Apparatus on the Basis of the Waveform Shapes

Next, the diagnostic apparatus (i) of the third embodiment will beexplained. This apparatus computes the distortion from the measurementdata of the pulse waveforms, decides the shape on the basis of thedistortion and performs diagnosis on the basis of the waveform shapes.

FIG. 27 is a block diagram showing the structure of this apparatus (i).The reference numeral 311 refers to a pulse wave detection device, andFIG. 28 illustrates the method of detection. In FIG. 28, S1 refers to apressure sensor for detecting the radial arterial waveforms of anexaminee. The numeral S2 refers to a cuff belt worn on the upper arm tomeasure the blood pressure. The pulse wave detection device 311 modifiesthe radial arterial waveforms with blood pressure, and outputs theresults as analogue electrical signals. In FIG. 27, the numeral 313refers to an A/D converter to covert the analogue signals outputted bythe pulse wave detection device 311 to digital signals. The numeral 314refers to a distortion calculator comprising a Fourier analyzer 315 anda distortion computation device 317. The Fourier analyzer 315 includesmicrocomputers and others, and the analytical programs for Fourieranalysis are stored in memories such as ROM. The Fourier analyzer 315analyzes the digital signals outputted from the A/D converter 313, andoutputs the amplitude Q₁ of the fundamental waveform, the amplitude Q₂of the second harmonics, . . . and the amplitude Q_(n) of the nthharmonics. The value of n is determined suitably depending on theamplitude of the nth harmonic distortion.

The distortion calculator 317 calculates the value of the distortionbased on the outputted amplitudes Q₁, Q₂ and Q_(n). The distortion valued is obtain from the expression:$d = \frac{\sqrt{{Q_{2}}^{2} + {Q_{3}}^{2} + \ldots + {Q_{n}}^{2}}}{Q_{1}}$

The numeral 319 refers to a waveform shape analyzer which determines theshape of the waveforms based on the distortion factor d outputted fromthe distortion calculator 314 such that:

1.161>d>0.960 defines the Hua mai type;

0.960>d>0.854 defines the Ping mai type; and

0.798>d>0.670 defines the Xuan mai type.

The waveform shape analyzer 319 either outputs the results of thedetermination of the waveform type according to the above definitions,or displays or prints on an F output device 321 that a waveform type isindeterminate.

In this case the diagnostic apparatus presented in Chapter 1 may be usedfor diagnostics by storing data (potential illness) relating thewaveform shapes to the conditions of the living body in the knowledgedata base 26, and reading out data (i.e. diagnosis) to correspond withthe results obtained from the waveform shape analyzer 319 of the thirdembodiment.

CHAPTER 3-2 Diagnostic Apparatus on the Basis of the CirculatoryParameters

Next, the diagnostic apparatus (ii) of the third embodiment will beexplained. This apparatus computes the distortion from the measurementdata of the pulse waves; computes the circulatory parameters by thedistortion; and performs diagnosis on the basis of these parameters.

The apparatus (ii) is shown in FIG. 29. In FIG. 29, those componentswhich are the same as in the apparatus (i) shown in FIG. 27 are giventhe same reference numerals, and their explanations are omitted.

The numeral 323 refers to a circulatory dynamic parameter calculator,and computes the values of the proximal section resistance R_(c), distalsection resistance R_(p), the momentum L and the compliance C on thebasis of the values of the distortion factor d calculated by thedistortion calculator 314. The circulatory dynamic parameters arecalculated from the following expressions.

R_(c)=58.68·d^(−0.394)

R_(p)=2321·e^(−0.615d)

L=162.8·e^(−2585d)

C=10⁻⁴(−1.607+3.342·d)

The units are the same as in the previous expressions in Chapter 2-1-1.

As explained above, by utilizing the relationship equations, it will bepossible to compute the circulatory dynamic parameters without using thepulse wave analysis apparatus described in Chapter 2. It is obvious thatthe computed dynamic parameters are also applicable to the firstembodiment described in Chapter 1.

The dynamic parameter calculator 323 determines the waveform type basedon the dynamic parameters.

In this apparatus (ii), the Hua mai type is defined by:

28.878<R_(c)<65.218

1005.4<R_(p)<1358.5

7.647<L<12.994 and

1.476×10⁻⁴<C<2.584×10⁻⁴,

the Ping mai type is defined by:

55.543<R_(c)<128.531

1158.2<R_(p)<1614.8

11.810<L<21.018 and

1.076×10⁻⁴<C<1.698×10⁻⁴,

the Xuan mai type is defined by:

164.958<R_(c)<287.228

1332.0<R_(p)<1834.0

22.157<L<32.943 and

0.612×10⁻⁴<C<1.026×10⁻⁴.

The dynamic parameter calculator 323 outputs the results of thedetermination through an output device 321.

It is obvious that the defined waveform types as parameters are alsoapplicable to the first embodiment.

CHAPTER 3-3 Diagnostic Apparatus on the Basis of Waveform Shapes andParameters

Next, the apparatus (iii) of the third embodiment will be explained.This apparatus computes the distortion from the measurement data of thepulse waves; by the distortion, computes the circulatory parameters anddetermines the waveform shape type; and performs diagnosis on the basisof these parameters and the shapes.

This apparatus (iii) is shown in FIG. 30. In FIG. 30, those componentswhich are the same as in the apparatus (i) or (ii) shown in FIG. 27 or29 are referred to by the same reference numerals, and theirexplanations are omitted.

The reference numeral 325 refers to a comprehensive analyzer, andperforms pulse wave analysis based on the entire results of the waveformshape analyzer 319 and the dynamic parameter calculator 323. Forexample, the waveform results by the waveform analyzer 319 and theparameters determined by the dynamic parameter calculator 323 may bestored in a memory table in the comprehensive analyzer 325 for its use.The output results may be one of the three waveform shape types, or thenames of the illness associated with that waveform. The output device321 displays or prints the results outputted from the waveform shapeanalyzer 319, from the dynamic parameter calculator 323, from thecomprehensive analyzer 325 and others. The user of the apparatus such asdoctors and others are thus able to obtain the diagnostic informationregarding the examinee.

Alternatively, a diagnosis may be performed in terms of the waveformsparameters in the first embodiment, determined on the basis of thewaveform shape obtained from the waveform shape analyzer 319 and thecirculatory dynamic parameters computed by the dynamic parametercalculator 323.

In the third embodiment, the distortion factor d may be defined in termsof the mathematical expression$\frac{Q_{2} + Q_{3} + \ldots + Q_{n}}{Q_{1}},$

or it may be defined in other ways, but the same relationship will beobtained. For example, the distortion factor d may be obtained by amethod illustrated in FIG. 41. In this method, the pulse waves areinputted into a low-pass filter 351 and a high-pass filter 354 to outputa low frequency component v1 and a high frequency component v2. Theoutputted signals v1, v2 are passed through rectifier circuits 352, 355and passed through smoothing circuits (normally used LPF) 353, 356 toobtain direct current signals w1, w2. The DC signals w1, w2 areforwarded to the division circuit 357 to obtain a value of thedistortion factor d=w2/w1.

CHAPTER 4 Stress Level and Physiological Age Evaluation Apparatus

Recently, stress and fatigue has come to be one of the main causes ofadult sickness, and so called death due to overwork. If the conditionsof stress and fatigue can be grasped, then through appropriateprecautionary measures taken at an early stage, the progression of theadult disease, and sudden death etc. can be prevented.

Presently there are few examination methods which can detect stress,fatigue and often physiological and psychological problem of a humanbody. Moreover, of these few examination methods, there are none whichenable simple examination. For example, some methods measure thecontents of catecholamine or cortisol included in the blood or urine, asan indication of physiological stress. However with these methods, ablood sample or a special assay method is necessary. The methods arethus not simple methods which can be made every day. Moreover, there isa method which measures the urine concentration of adrenocorticalhormone metabolism production as an indication of stress. However, thismethod also cannot be considered simple since a urine sample isrequired. Moreover, the reliability as an examination method has yet tobe established. The so called Claris system diagnostic questionnaire ofthe B&M company was an established method of measuring psychologicalstress. However this diagnostic questionnaire had 81 question items,thus imposing a heavy burden on the patient or the diagnostician at thetime of questioning. Additionally, there has been a need for a devicewhereby one can easily perform of his own physiological age as well asstress level.

In view of the problems described above, the present inventors selectedthe peak points of the waveforms to be representative of the waveformparameters to be used in the determination of psychosomatic stresslevels and physiological age, and produced a diagnostic apparatus of afourth embodiment.

The application of the diagnosis of the present invention is not limitedto the stress level or physiological age, further the parameters are notlimited to disclosed waveform parameters used to the diagnosis in theembodiment of the invention. For other diagnoses, some suitablediagnostic apparatus can be developed using the same approach aspresented in the following.

The peak points of the waveforms obtained by this diagnostic apparatuscan be applicable to the first embodiment for the waveform parameters.

In this Chapter, the diagnostic apparatus according to a fourthembodiment of the present invention will be explained.

CHAPTER 4-0 Pre-examinations

The present inventor carried out the following pre-examinations whendesigning the device for stress evaluation.

CHAPTER 4-0-1 Characteristics for Substitutional Parameters

In order to carry out the stress evaluation without imposing a heavyburden on the examiner or the procedure, substitute parameters forstress parameters such as blood plasma catecholamine values, whichreflect the stress level are necessary. The present inventor observedthat waveforms of pulse waves change, due to physiological stress,physiological age and psychological stress, and selected waveforms ofpulse waves as candidates for parameters for use in stress evaluation.In the process, the radial arterial pulses of 53 examinees was measured,and the following information, i.e., the peak points (inflection points)of pulse waveform was collected as characterizing waveform parameters toanalyze the problem.

(a) The period T₆, which represents the time for one pulsation cyclefrom the rise of one pulsation (in the following, the time of this riseis referred to as the pulse wave initiation time) and the next pulsationrise.

(b) The blood pressure values y₁˜y₅, representing a maximum point P₁, aminimum point P₂, a maximum point P₃, a minimum point P₄, and a maximumpoint P₅ appearing successively in the pulse waves.

(c) The elapsed periods T₁˜T₅, corresponding to time period from thepulse wave initiation time to the appearance of the respective pointsP₁˜P₅.

Refer to FIG. 42 for the above.

Moreover, the present inventor observed that conscious symptoms appearwhen the stress level became high, and measured psychosomatic fatiguelevel using the psychosomatic fatigue level diagnostic questionnaireshown in FIG. 43. The questions in the diagnostic questionnaire were toascertain whether the patients was conscious of the various symptomswhich are prominent at high stress levels. The examinee selected one of;never, sometimes, often, or always as a reply to the questions. Here thepoints for the respective replies were:

never at “0”; sometimes at “1”; often at “2”; and always at “3”.

With an affirmative reply to a question, that is to say, a higher replylevel for the degree of consciousness of the symptom, proportionallyhigher points were obtained. The total points obtained for the patient'sselected answers become the psychosomatic fatigue level M.

CHAPTER 4-0-2 Reference Values for Stress Levels

The blood plasma catecholamine value has been recognized in the past asa stress index of physiological stress. Therefore the blood plasmaadrenaline densities AD (ng/ml), and the blood plasma nor adrenalinedensities NA (ng/ml), in the blood of 53 examinees were measured, andbecame the reference value for the physiological stress of each of theexaminees.

For the psychological stress, a diagnostic questionnaire with 81headings (B & M Claris System) was made for each of the examinees. Theresults of this became the reference value MS for the psychologicalstress level of the examinee.

CHAPTER 4-0-3 Correlation Analysis

A correlation analysis was made among the respective parameters obtainedfor each examinee in the above Chapter 4-0-1, and in the physiologicalstress level and psychological stress level obtained in the aboveChapter 4-0-2.

(1) Physiological Stress

Initially, in making a correlation analysis of the blood plasmacatecholamine value, and the waveform parameters, the following equationwas obtained as a relationship equation with a high correlationcoefficient “r”,

NA(ng/ml)=−0.44(T ₅ −T ₁)+1.07  (51)

with main correlation coefficient r=0.44 (probability p<0.000001, Fvalue=25.42).

It was confirmed that with this equation as an indication ofphysiological stress level, the blood plasma nor adrenaline value couldbe estimated on the basis of the waveform parameters T₁ and T₅. In thepresent embodiment, the physiological stress level is calculated bycalculating out the right side in equation (51).

In making a correlation analysis including not only the waveformparameters but also the psychosomatic fatigue level M, the followingrelationship equation was obtained,

NA(ng/ml)=0.46M+0.24y ₁ /T ₁  (52)

with

r=0.51, (p<0.000001, F=12.47).

Also including the psychosomatic fatigue level M as a parameter in thisway was confirmed to give a more accurate value for the estimation ofthe physiological stress level. In the present example, when it ispossible to obtain the psychosomatic fatigue level M, the physiologicalstress level is calculated by calculating the right side in equation(52).

(2) Psychological Stress

In making a correlation analysis of the reference value MS for thepsychological stress, the waveform parameters and the psychosomaticfatigue level M, the following equation was obtained as a relationshipequation with a high correlation coefficient. $\begin{matrix}{{MS} = {{0.45M} + \frac{0.29\left( {T_{4} - T_{1}} \right)}{T_{6}} - 14.83}} & (53)\end{matrix}$

with

r=0.56, (p<0.000001, F=21.61).

In the present embodiment, the psychological stress level is calculatedby carrying out the right side calculation in equation (53).

(3) Physiological Age

When the correlation relationship between the age Y of the examinee, andthe waveform parameters was investigated, it was found that acorrelation coefficient existed between both. $\begin{matrix}{Y = {{{- 33.74}\left( {T_{5} - T_{4}} \right)} + {61.64\frac{T_{1}}{T_{6}}} - {8.0678\frac{\left( {T_{5} - T_{4}} \right)}{T_{6}}} + 33.324}} & (54)\end{matrix}$

with

r=0.56, (p<0.00000, F=12.609).

CHAPTER 4-1 Diagnostic Apparatus (i)

Next, the diagnostic apparatus (i) in accordance with the fourthembodiment of the present invention will be explained.

This apparatus performs diagnosis of physiological and psychologicalstress levels; and physiological age of the examinee on the base of theinputted parameters of his pulse waveforms.

CHAPTER 4-1-1 Structure of the Diagnostic Apparatus (i)

FIG. 44 shows the structure of the apparatus according to the apparatus(i). In this Figure, numeral 401 indicates a micro-computer, forcontrolling the operation of the respective components of the apparatus,and for carrying out a diagnosis of the physiological stress level,psychological stress level and physiological age according to the aboveequations (52), (53) and (54). Numeral 402 indicates a keyboard which isused as an input means for command of the micro-computer 401, and forthe input of parameters for diagnosis. Numeral 403 indicates a FDD(floppy disk drive unit) provided as a parameter input means in the caseof a large number of examinees. The examiner installs a FD, on which isstored the parameters for the various examinees, into the FDD 403.Consequently, the parameters for all examinees can be transferred to themicro-computer 401 as a batch. The means for storage of the parametersto be inputted to the apparatus is not limited to a magnetic disk suchas a floppy disk, and disks such as optical magnetic disks may be used.Numeral 404 indicates a display apparatus such as a CRT, which displaysthe messages and stress level diagnosis results output from themicro-computer 401, for viewing by the examiner. Numeral 405 indicates alarge capacity storage unit provided for storing the diagnosis resultsof the stress levels etc., and the parameters for use in the diagnosis,serially for each examinee. Numeral 406 indicates a printer for theoutput of diagnosis results such as stress level.

CHAPTER 4-1-2 Operation of the Diagnostic Apparatus (i)

On switching on the power supply to the diagnostic apparatus (i), aninitialization process is carried out by the micro-computer 401, and amenu screen for prompting the selection of either the keyboard 402 orthe FDD 403 for carrying out the parameter input, appears on the displaydevice 404. The examiner inputs a command from the keyboard, and selectsthe desired input configuration.

(1) Parameter Input

When the keyboard input configuration is selected, the examiner inputssuccessively by way of keyboard 402, the identification information forthe examinee, the parameters necessary for evaluation, that is to saythe waveform parameters and psychosomatic fatigue level obtained by theabove fatigue level diagnostic questionnaire, and the year, month andday of collection of these parameters. This information is successivelyinputted to the buffer memory inside the micro-computer 401.

On the other hand, when the FDD input configuration is selected, theexaminer inserts into the FDD 403, the floppy disk on which is storedthe identifying information for each examinee, the parameters necessaryfor evaluation of stress level etc., and the year, month and day ofcollection of these parameters, and inputs a command from the keyboard402 directing input from the floppy disk to the buffer memory. As aresult, the information corresponding to each of the examinees on the FDis input sequentially from the FDD 403 to the buffer memory inside themicro-computer 401.

(2) Diagnosis of Stress Level (and the Like)

On completion of input of the above mentioned parameters, the parametersin the buffer memory for diagnosis of the stress of each examinee, aresubstituted into the above mentioned equations (52), (53) and (54) toobtain the physiological stress level, psychological stress level andphysiological age for each of the examinees. The resultant physiologicaland psychological stress levels and physiological age for each of theexaminees are stored temporarily in the buffer memory. Furthermore, thestress level for each of the examinees and the parameters used forcalculation of the stress levels are displayed for each examinee on thedisplay device 404.

(3) Storage of Diagnosis Results

On completion of the diagnosis, the examiner directs storage of thediagnosis results from the keyboard 402, so that the information in thebuffer memory corresponding to each of the examinee, is successivelywritten to the large capacity storage unit 405. Then, more specifically,with the present apparatus, the diagnosis results such as stress level,and the information used in the diagnosis are partitioned for eachexaminee, and stored. The information related to the respectiveexaminees that is read from the buffer memory, is added to the end ofthe previously stored information corresponding to the respectiveexaminees in the large capacity storage unit 405.

(4) Print Out of Diagnosis Results

When the examiners inputs from the key board 402, the command for outputof the diagnosis results, the micro-computer 401 sends theidentification information and stress levels for each of the examineeswhich are stored in the buffer memory, to the printer 406 for print out.Furthermore, if the examiner inputs identification information for aspecific examinee, together with a command for a time series display ofthe stress levels, the micro-computer 401 reads from the large capacitystorage unit 405, the stress levels obtained by a predetermined numberof previous diagnosis corresponding to the selected examinee, and thecollection year month and day of the parameters used in the stressdiagnosis. The micro-computer 401 then generates data for printing agraph showing the time change of stress level, and sends this to theprinter 406. As a result, the printer 406 prints out the stress leveltime changes for the selected examinee.

CHAPTER 4-2 Diagnostic Apparatus (ii)

Next, the diagnostic apparatus (ii) in accordance with the fourthembodiment.

This apparatus (ii), adds to the apparatus (i) described in Chapter 4-1,a means for measuring the pulse wave of the examinee, and a means fordetecting the waveform parameters from these pulse waves, therebyenabling the collection of parameters from the examinee, and stressevaluation to be carried out simultaneously.

CHAPTER 4-2-1 Structure of the Diagnostic Apparatus (ii)

FIG. 45 is a block diagram showing the structure of a diagnosticapparatus. In this figure, components corresponding to those of theapparatus (i) explained in Chapter 4-1 are indicated by the same symbolsand description is omitted.

In FIG. 45, numeral 411 indicates a pulse wave detection apparatus,which detects the radial pulse waveform by means of a pressure sensorattached to the examinee's wrist (not shown on the figure), and outputsa pulse wave signal (analog signal). Numeral 412 indicates a parametersampling section, which processes signals under micro-computer 401control, to extract waveform parameters necessary for diagnosis of thestress level, from the pulse wave signal output from the pulse wavedetection apparatus 411. Numeral 413 indicates a mouse, which isconnected to the micro-computer 401, and acts as a designation devicewhen manually designating the waveform parameter, without using theparameter sampling section 412.

The following is a description of the construction of the parametersampling section 412, with reference to FIG. 46. In FIG. 46, numeral 501indicates an A/D (analog/digital) converter which converts the pulsewave signal output by the pulse wave detector 411, into a digitalsignal, in accordance with a sampling clock f of a fixed period, andoutputs this. Numeral 502 indicates a low pass filter which carries outprocessing to eliminate components of the successively output digitalsignal from the A/D converter 501, that are above a predeterminedcut-off frequency. The result is successively outputted as waveformvalues W. Numeral 503 indicates a waveform memory comprising a RAM(random access memory) which successively stores the waveform values Wsupplied by way of the low pass filter 502. Numeral 511 indicates awaveform address counter which counts the sampling clock f during theperiod when the waveform collection directive START from themicro-computer 401 is outputted. The count results are output aswaveform addresses ADR1 into which the waveform values W are to bewritten. Numeral 512 indicates a selector which selects the waveformaddresses ADR1 output by the waveform address counter 511, when themanual output mode signal MAN is not outputted, and supplies these tothe address input terminal of the waveform memory 503; and selects theread addresses ADR4 outputted by the microcomputer 401, when the manualoutput mode signal MAN is outputted, and supplies these to the addressinput terminal of the waveform memory 503.

Numeral 521 indicates a differentiating circuit which computes the timedifferentials of the waveform values W which are successively outputfrom the low pass filter 502, and outputs these. Numeral 522 indicates anull cross detection circuit which outputs a null cross detection pulseZ when the time differential of the waveform value W is “0” due to thewaveform value W being a maximum value or a minimum value. Numeral 523indicates a peak address counter which counts the null cross detectionpulse Z during the period when the waveform collection directive STARTfrom the micro-computer 401 is outputted. The count results areoutputted as peak addresses ADR2. Numeral 524 indicates an averagemovement computation circuit which computes, up to the present timepoint, the mean value of the time differential values of a predeterminednumber of previous waveform values W, which are outputted from thedifferentiating circuit 521, and outputs the result as slope informationSLP which shows the slope of the pulse waves up until the present timepoint. Numeral 525 indicates a peak information memory (to be discussedlater) for storing peak information.

The micro-computer 401 carries out the following control steps based onthe information inputted from the respective elements described above.

(1) Peak Information Editing

The differentiation circuit 521, and the null cross detection circuit522 inside the parameter sampling section 412, obtain the followinglisted information for each detection of a waveform peak point. Thisinformation is written to the peak information memory 525 as peakinformation.

Contents of the Peak Information

(1)-1: Waveform value address ADR1:

This is the write address ADR1 which is output from the waveform addresscounter 511 at the time point when the waveform value W outputted fromthe low pass filter 502, becomes a maximum or minimum value. That is tosay, the write address in the waveform memory 503 for the waveform valueW corresponding to the maximum or minimum value.

(1)-2: Peak classification B/T:

This is information which indicates whether a waveform value W writtento a waveform value address ADR1 is a maximum value T (Top), or aminimum value B (Bottom).

(1)-3: Waveform value W:

This is the waveform value corresponding to the maximum value or theminimum value.

(1)-4: Stroke STRK:

This is the change portion of the waveform value, from the immediatelypreceding peak value to the present peak value.

(1)-5: Slope information SLP:

This is the mean value of the time differential of the predeterminednumber of previous waveform values up until the present peak value.

On the stress level diagnosis, the microcomputer 401 shifts to thefollowing operational mode.

(a) Automatic Diagnosis Mode

Reads the storage contents of the peak information memory 525, generatesthe waveform parameters, and carries out the stress level diagnosis in asimilar manner to that of the first working diagnostic apparatus (i).

(b) Manual Designation Mode

Displays the waveform stored in the waveform memory 503 on the displaydevice 404, detects the waveform peak point designated by operator mouseoperation, and carries out the computation of the waveform parametersand diagnosis of the stress level, on the basis of the results.

CHAPTER 4-2-2 Operation of the Diagnosis Apparatus (ii)

The following is a description of the operation of the Diagnosisapparatus.

(a) Automatic Diagnosis Mode

(a)-(1) Collection of Waveform and Peak Information

Initially, on input by way of keyboard 402 of a command to obtain thestress level, the micro-computer 401 outputs a waveform collectiondirective START, and releases the reset of the waveform address counter511 and the peak address counter 523, in the parameter sampling section412.

As a result, the waveform address counter 511 starts counting thesampling clock f, and the count value is supplied via the selector 512,to the waveform memory 503 as a waveform address ADR1. The radialarterial pulse waveform detected by the pulse wave detector 411 is inputto the A/D converter 501, and converted sequentially into a digitalsignal according to the sampling clock f, and then outputtedsequentially as waveform values W, via the low pass filter 502. Thewaveform values W outputted in this way are supplied sequentially to thewaveform memory 503, and written to a memory area designated by thewaveform address ADR1 at that time point. By means of the aboveoperation, one row of waveform values W corresponding to the radialpulse waveform illustrated in FIG. 48, are stored in the waveform memory503.

Detection of the peak information, and writing to the peak informationmemory 525 is carried out in parallel with the above operation asdescribed below.

Initially the time differential of the waveform value W output from thelow pass filter 502, is computed by the differentiating circuit 521.This time differential is then input to the null cross detection circuit522 and the mean movement calculating circuit 524. The mean movementcalculating circuit calculates the mean value (that is to say meanmovement value) of the predetermined number of previous timedifferentials for each time differential value of this type of waveformvalue W supplied, and the calculated result is output as slopeinformation SLP. Here, when the waveform value W is increasing or has amaximum condition after increasing, a positive value is outputted as theslope information SLP, while when decreasing or with a minimum valueafter decreasing, a negative value is output as the slope informationSLP.

On output of the waveform value W corresponding to the maximum point P₁as shown in FIG. 48, from the low pass filter 502, a “0” for the timedifferential is outputted from the differentiating circuit 521, and anull cross detection pulse Z is outputted from the null cross detectioncircuit 522.

As a result, the micro-computer 401 fetches, the waveform address ADR1being the count value of the waveform address counter 511, the waveformvalue W, the peak address ADR2 being the count value of the peak addresscounter (in this case ADR2=“0”), and the slope information SLP, for thattime point. Due to the output of the null cross detection signal Z, thecount value ADR2 of the peak address counter 523 becomes “2”.

Subsequently, the micro-computer 401 creates a peak classification B/Tbased on the symbol of the fetched slope information SLP. In this case,since positive slope information is outputted at the time point when thewaveform value W for the maximum value P₁ is outputted, themicro-computer 401 sets the value of the peak information B/T to onecorresponding to a maximum value. The micro-computer 401 then designatesthe peak address ADR2 (in this case ADR2=0) as fetched from the peakaddress counter 523, as the write address ADR3, and writes the waveformvalue W, the waveform address ADR1 corresponding to the waveform valueW, the peak classification B/T, and the slope information SLP, into thepeak information memory 525 as first peak information. In the case ofwriting the first peak information, since there is no peak informationimmediately prior to this, then the creation and writing of strokeinformation is not carried out.

Subsequently, on output of a waveform value W corresponding to theminimum point P₂ as shown in FIG. 48, from the low pass filter 502, anull cross detection pulse Z is outputted in a similar manner to theabove, and the write address ADR1, waveform value W, peak address ADR2(=1), and the slope information SLP (<0) are fetched by themicro-computer 401. Subsequently, the micro-computer 401 determines thepeak classification B/T (in this case bottom B) based on the slopeinformation SLP in a similar manner to the above. Moreover, themicro-computer 401 supplies an address that is one smaller than the peakaddress ADR2, to the peak information memory 525 as a read out addressADR3, and reads out the first written waveform value W. Then, themicro-computer 401 calculates the difference between the waveform valueW fetched this time from the low pass filter 502, and the first waveformvalue W read from peak information memory 525, to obtain the strokeinformation STRK. The peak classification B/T, and stroke informationSTRK obtained in this way are written together with other informationADR1, W, slope information SLP, as second peak information, to an areacorresponding to the peak address ADR3=1 of the peak information memory525. The subsequent operations for when the peak points P₃, P₄ etc. aredetected, are carried out in a similar manner.

Then after the elapse of a predetermined period, the output by themicro-computer 401, of the waveform collection directive START isstopped, terminating collection of the waveform values W and peakinformation.

(a)-(2) Waveform Parameter Sampling

Prior to waveform parameter extraction, the micro-computer 401 carriesout a process to specify information corresponding to waveforms of onewave length, for collecting the waveform parameters from amongst thevarious information stored in the peak information memory 525.

Initially the slope information SLP and stroke information STRKcorresponding to respective peak points P₁, P₂ etc. are successivelyread out from the peak information memory 525. After this, strokeinformation corresponding to a positive slope (that is to saycorresponding to slope information SLP with a positive value) isselected from amongst the respective stroke information STRK. Then, fromamongst this stroke information, a predetermined number of higher rankstroke information having large values is further selected. After this,one corresponding to a middle values is selected from amongst theselected stroke information STRK, and the stroke information is obtainedfor the rising part of the pulse wave of one wave length portion whichis to be subjected to waveform parameter extraction, for example therising portion indicated by symbol STRKM in FIG. 48. Subsequently thepeak address one prior to the peak address of the said strokeinformation is obtained. That is to say, the peak address of the startpoint P₆ of the pulse wave of the one wave length portion which is to besubjected to waveform parameter extraction.

Next the micro-computer 401 refers to the respective peak information inthe peak information memory 525, which corresponds to the pulse wave ofone wave length portion, and computes respective peak information forsubstitution into the beforementioned computational equations (51)˜(54).For example the following information.

y₁: y₁ is the waveform value y₁ corresponding to peak point P₇.

T₁: T₁ is calculated by subtracting the waveform address correspondingto peak point P₆ from the waveform address corresponding to peak pointP₇, and multiplying the result by the period of the sampling clock Ø.

T₄˜T₆: T₄˜T₆ are calculated in a similar manner to T₁, based on thedifference between the waveform addresses of the respective peak points.

The respective parameters obtained in this way are stored in the buffermemory.

(b) Manual Directive Mode

With the diagnostic apparatus (ii), it is possible to set a manualdirective mode (a) using keyboard 402 operation, in addition to theabove automatic diagnosis mode. When this manual directive mode is set,the examiner can designate by operation of a mouse, the peak points ofthe pulse waves necessary for the calculations of the waveformparameters. That is to say, according to the following.

In the manual directive mode, after outputting the waveform collectiondirective START for a predetermined time, the micro-computer 401 outputsa manual mode signal MAN. Then, read addresses ADR4 increasingsuccessively from “0” are output by the micro-computer 401, and suppliedto the waveform memory 503 by way of the selector 512. Radial pulsewaveforms stored in the waveform memory 503 are thus read out anddisplayed on the display device 404.

Through operation of the mouse 413, the examiner moves the cursorposition on the display device 404, and successively indicates the firstpoint and last point of the pulse wave, and the various maximum andminimum points of the pulse wave with a click input. The micro-computer401 detects the mouse operation, reads from the waveform memory 503digital signals corresponding to the first point and last point, and therespective maximum and minimum points of the pulse wave designated bythe examiner, and extracts the necessary waveform parameters (see theabove equation (52) and (53)) from the read out information, and storesthese in the buffer memory.

(c) Psychosomatic Fatigue Level Input

On completion of the waveform parameter collection through either of theabove (a) or (b) mode, the micro-computer 401 displays the psychosomaticfatigue level diagnostic questionnaire shown in FIG. 43 on the displaydevice 404 in accordance with the keyboard or mouse directive of theexaminer. The examiner then makes a question diagnosis of the examineecorresponding to the displayed questions diagnosis table, and inputs theexaminees response to the micro-computer 401 by mouse 413 operation.Here the question diagnosis may be a dialogue form of input. That is tosay, each question on the diagnostic questionnaire is displayed one attime, or outputted as a voice, and the answer corresponding to this cantake the format of examinee input by a keyboard or the like, to themicro-computer 401. The micro-computer 401 calculates the psychosomaticfatigue level on the basis of the input answers, and writes the resultinto the buffer memory.

All of the information necessary for this stress evaluation is arrangedin the buffer memory as above. The micro-computer 401 makes a stresslevel diagnosis based on the information stored in the buffer memory,and thereafter the results are outputted and stored under the directiveof the examiner in a similar manner to the apparatus (i) in explained inChapter 4-1.

CHAPTER 4-3 Diagnostic Apparatus (iii)

Next is a description of a diagnostic apparatus (iii). This stress leveldiagnostic apparatus has a color display device (not shown in thefigure) as a stress level display means, in addition to the constructionto the apparatus (ii) explained in Chapter 4-2. The micro-computer 401in this apparatus, after calculating the physiological stress level andthe psychological stress level, determines the display color accordingto the illustrated table of FIG. 49, and displays this on the colordisplay unit.

The physiological stress level, psychological stress level andphysiological age are obtained and these may be color displayed. In thiscase, rather than the two dimensional table shown in FIG. 49, a threedimensional display defining colors corresponding to the respectivecombinations of physiological stress level, psychological stress leveland physiological age, can be used to determine the display color.

With the present apparatus, the combined stress levels of thephysiological stress level and psychological stress level are indicatedby the display color of the color display device. Hence even the generalpublic, who have no judgment basis with respect to numerical values ofstress level, can easily confirm their own stress level.

With the above apparatus, the examinee can use it as an automatic systemfor diagnosing his/her own stress level, without the need for a examinersuch as a doctor.

CHAPTER 4-4 Variation of the Fourth Embodiment

The fourth embodiment is not limited to the above diagnostic apparatuses(i) to (iii). For example, a number of variations such as given beloware also possible.

Apparatus (iv)

With the above apparatuses, both the waveform parameter and thepsychosomatic fatigue level are used as parameters, and both thephysiological stress and the psychological stress diagnosis performed.However, it is also possible to have a construction wherein only thephysiological stress or physiological age are evaluated based on onlythe waveform parameter according to equation (51) or equation (54). Inthis case, since the effort of input of the psychosomatic fatigue levelis omitted, use of the apparatus is simplified.

Apparatus (v)

In the above respective apparatuses, the stress level is performed ofdiagnosis on the basis of the examinees radial arterial pulse wave.However, the arterial pulse wave can be measured at locations from theradial portion to the finger portion, and the stress level diagnosisperformed on the basis of this arterial pulse wave.

Apparatus (vi)

In the above apparatus (iii), a structure was adopted wherein the stresslevel etc. was made visible by means of display colors. However, thestress level display means is not limited to this. For apparatus, in asituation wherein the examinee recognizes the stress level in a visualsense, the stress level may be represented by the shading of the displaycolor. It is also possible to display character information describingthe stress level. Moreover, the display is not limited to visual methodsof expression, and it may be possible to have a method wherein thestress level is expressed by appealing to a sense of hearing. Forexample, the pitch, volume, and tone of the sound may be changeddepending on the stress level etc., and played to the examinee. Also, avoice output explaining the evaluation results of the stress level etc.is possible. Music may be provided corresponding to the stress leveletc., such as bright music when the stress level is low and gloomy musicwhen the stress level is high.

In Chapter 4, the apparatus for performing diagnosis for the stresslevel and the physiological age were presented. Utilizing the methodused in the above apparatus, a diagnostic apparatus for other subjectscan be structured.

In this case, the waveform parameters which have the highest correlationfor the diagnostic subject may be used. For example, the dynamiccirculatory parameters described in Chapter 2, the pulse waveformspectrum described in Chapter 1, and so on, may be used as waveformparameters.

The means for obtaining the wavefom parameter used to diagnose is notlimit to the above apparatuses, and may be selected so as to befavorable to obtaining required parameter.

For example, there are the two methods to obtain the circulatory dynamicparameters; using the electrical model in Chapter 2, and computing thedistortion factor of pulse waveform in Chapter 3. Either of the twomethods may be favorably selected by considering the operational speed,accuracy, and so like for requirement.

As explained, diagnosis for the stress level can be accurately performedconsidering the psychosomatic fatigue level. Similarly, there are caseswhen a diagnosis may be more accurately performed by the taking theconscious symptom of the examinee into consideration. In this case, byadding inputting means for inputting conscious symptoms in thediagnostic apparatus, diagnosis may be performed based on both theinputted conscious symptom and waveform parameter of the pulse wave.

Moreover, depending on the diagnostic subjects, there are cases when itis wanted not only simply the name of disease but also the seriousnessof the disease and outputting the computed degree. In such a case, usingvisual data (color, density, character and so on) and/or the audio data(music, voice and so on), diagnostic apparatus may express and outputthe degree of seriousness of the disease (stress level in the diagnosticapparatus of the fourth embodiment). Diagnosis for each predeterminedperiod my depends on the diagnosis contents.

CHAPTER 5 Pulse Wave Analyzing Apparatus for Analyzing Spectrum of PulseWaves

Recently, pulse diagnosis has come to the public attention, resulting inintensified research to explore the health condition of the body basedon pulse waves. As general waveform analyzing techniques, there aretechniques such as the FFT frequency analysis technique, and pulse waveanalysis using this type of frequency analyzing technique is underinvestigation.

A pulse waveform is not the same shape for all pulses, and changesmoment by moment. Moreover, the wavelength of each pulse wave is notconstant. A technique has been considered wherein a pulse wave havingsuch chaotic (random) behavior is considered as a waveform having anextremely long period, and subjecting it to a Fourier transformation.With such a technique, a detailed waveform spectrum can be obtained,however since the amount of computation becomes immense, the techniqueis not suited for use in rapidly obtaining the spectrum of pulse wavesoccurring moment by moment. If wave parameters representing thecharacteristics of the separate waves making up the pulse wave can beobtained continuously, then a much greater amount of informationrelating to a living body can be obtained. However a device to meet suchrequirements is presently not available.

Therefore, the one of objectives is to provide an apparatus foranalyzing the characteristic of each individual pulse waves rapidly.Furthermore, the fifth embodiment enables higher performance to beachieved in the various apparatuses presented in Chapter 1 to 5.

In the following, the pulse wave analysis apparatus according to thefifth embodiment will be explained.

CHAPTER 5-1 Pulse Wave Analyzer (i)

This analyzer performs computation of spectrum of pulse waves for eachpulsation.

CHAPTER 5-1-1 Structure of the Analyzer (i)

FIG. 50 shows the structure of a pulse wave analyzer according to thefifth embodiment of the present invention. As is shown in the FIG. 50,the pulse wave analyzer comprises a pulse wave detector 601, an inputunit 602, an output unit 603, a waveform sampling memory 604, afrequency analyzing unit 605 and a micro-computer 606 which controls allof these.

The pulse wave detector 601 comprises a strain gauge or the like, whichcan be pressed against an examinee's radial artery to detect thepressure, and output this as a pulse wave signal (analog signal). Theinput unit 602 is a device provided for command input such as a keyboardto the micro-computer 606. The output unit 603 comprises a printer,display devices and other. These devices come under the control of themicro-computer 606 and store, display etc. the pulse wave spectrumobtained from the examinee. The waveform sampling memory 604, undercontrol of the micro-computer 606, successively records the waveformsignals output from the pulse wave detector 601, and also extracts andstores information showing the change points in the pulse wave signal,that is to say the point of change from a pulse wave corresponding toone pulse to the pulse wave corresponding to the next pulse. The detailstructure of the waveform sampling memory 604 is same as the structureof the waveform sampling section 412.

The frequency analyzing unit 605 gives a repeating high speed playbackof the pulse wave signal stored in the waveform sampling memory 604, foreach pulsation, and obtains and outputs the spectrum making up the pulsewave for each pulsation. FIG. 51 shows details of the construction. Thepulse wave spectrum for each respective pulsation obtained from thefrequency analyzing unit 605, is fetched by the microcomputer 606 andoutputted from the output unit 603.

CHAPTER 5-1-1-1 Structure of the Waveform Sampling Memory 604

The waveform sampling memory 604 may use the parameter sampling section412 with its signals and information shown in FIG. 46. The explanationof the waveform sampling memory 604 is omitted to avoid duplication. Itis maintained that the manual output mode signal MAN shown is replacedwith the select signal S11, and the numeral 401 is replaced with 606 forthe micro-computer.

CHAPTER 5-1-1-2 Structure of the Frequency Analyzing Unit 605

Next is a detailed description of the construction of the frequencyanalyzing unit 605, with reference to FIG. 51. The frequency analyzingunit 605 receives, a waveform value WD for a pulse wave from thewaveform memory 503 in the waveform sampling memory 604, by way of themicro-computer 606. The received waveform value WD is repeatedly playedback at high speed, and the frequencies are analyzed for each pulse tocompute spectrums for the pulse waves. Moreover, the a frequencyanalyzing unit 605 serially computes respective spectrums whichconstruct the pulse waves, in the order of an initial basic spectrum ofthe pulse wave, following by the second harmonic wave spectrum, and soon.

When the first waveform value WD for the waveform of one pulse componentis output to the frequency analyzing unit 605, the micro-computer 606outputs a synchronizing signal SYNC and an integer N of the waveformvalue WD which is included in that pulse, and changes the select signalS12. Furthermore, during the output of the waveform value WD for onepulse component, the micro-computer 606 successively outputs writeaddresses ADR5 changing from “0” through to “N−1”, synchronously withthe transfer of the respective waveform values WD.

Buffer memories 201, and, 202 are provided for storing the waveformvalues WD outputted from the micro-computer 606. A distributor 721 takesa waveform value WD for a pulse wave from the sampling memory 604supplied via the micro-computer 606, and outputs this to one of buffermemory 701 or 702 as designated by a select signal S12. Furthermore, aselector 722 selects from the buffer memories 201, 202, the buffermemory designated by the select signal S2, and a waveform value WH readfrom the selected buffer memory is outputted to the high speed playbackunit 730 (to be described later). Selectors 711 and 712 select the writeaddresses ADR5, or the read addresses ADR6 (to be mentioned later)generated by the high speed playback unit 730, according to the selectsignal S12, so that each is supplied to the respective buffer memory 701and 702.

By switching control the above described distributor 721, selector 722,and 701 and 702 on the basis of the select signal S12, data is read fromthe buffer memory 702 and supplied to the high speed playback unit 730,while writing data to buffer memory 701 and while writing data to thebuffer memory 702, data is read from the buffer memory 701 and suppliedto the high speed playback unit 730.

The high speed playback unit 730 is a means for reading from the buffermemories 701 and 702 the waveform values corresponding to the respectivepulses. The read addresses ADR6 are changed in the range from “0” to“N−1” (where N is the number of waveforms to be read). Morespecifically, the high speed playback unit 730 generates read addressesADR6 during the period when each waveform value WD corresponding to acertain pulse is being written to one buffer memory, and repeatedlyreads over a number of times from the other buffer memory, all thewaveform values WD corresponding to the pulse before that pulse. At thistime, the generation of the read addresses ADR6 is controlled so thatall of the waveform values WD corresponding to one pulse are read outnormally within one fixed period. The period for reading all of thewaveform values for one pulse is changed to correspond to the level ofthe spectrum to be detected, with a change to T when a basic wavespectrum is detected, a change to 2T for a second harmonic spectrum, achange to 3T for a third harmonic spectrum, and so on. Moreover, thehigh speed playback unit 730 has an internal interpolator whichinterpolates the waveform values WH read from the buffer memory 701 or702, and outputs this as a waveform value of a predetermined samplingfrequency m/T (m is a predetermined integer).

A band pass filter 750 is a filter having a central frequency of apredetermined value 1/T. A sine wave generator 740 is a variablefrequency waveform generator and comes under control of themicro-computer 606. It sequentially outputs respective sign waves ofperiods T, 2T, 3T, 4T, 5T and 6T corresponding to the spectrum level tobe detected. A spectrum detection unit 760 detects respective pulseamplitudes H₁ to H₆ of each spectrum of the pulse wave, on the basis ofthe output signal level from the band pass filter 750, and detects therespective spectrum phases θ₁ to θ₆ on the basis of the differencebetween the phase of the band pass filter 750 output signal and thephase of the sine wave output by the sine wave generator 740.

CHAPTER 5-1-2 Operation of the Analyzer (i)

The following is a description of the operation of the presentembodiment shown in FIGS. 46, 50 and 51.

Initially, on input of a frequency analysis start command from the inputunit 602, a waveform collection directive START is outputted by themicro-computer 606, and the waveform address counter 511 and the peakaddress counter 523 the inside the waveform sampling memory 604 arereset.

(1) Waveform Division

As a result, the waveform address counter 511 starts counting thesampling clock f, and the waveform sampling memory 604 carries out in asimilar manner of the waveform section 412 explained at the index(a)-(1) in Chapter 4-2-2.

In other words, the waveform values W output in this way are suppliedsequentially to the waveform memory 503, and written to a memory areadesignated by the waveform address ADR1 at that time point P₁ to P₃.

In this analyzer, when the STRK is above a predetermined value, or morespecifically, when the STRK is considered sufficiently close tocorrespond to that for the rising portion of the pulse wave (STRKM inFIG. 48), then the micro-computer 606 reads the waveform address for theminimum value stroke start point (STRKM start point P₆ in FIG. 48) fromthe peak information memory 525, and writes this to the internal shiftregister. The subsequent operations for when the peak points P₃, P₄ etc.are detected, are carried out in a similar manner.

(2) Wave Shape Transfer

In parallel with the above operation, the micro-computer 606successively reads the waveform values from the waveform memory 503inside the waveform sampling memory 604, and transfers these to thefrequency analyzing unit 605 as waveform data WD. The operation isdescribed below with reference to FIGS. 52 and 53.

As shown in FIG. 53, the select signal S11 is changed synchronously withthe clock phase, and the waveform memory 503 synchronously, carries outa mode switching between the write mode and read mode.

In FIG. 52, when the waveform value of the pulse wave W_(n) of one pulseportion corresponding to a certain pulsation, is inputted to thewaveform memory 503, then at first the null cross detection signal Z isgenerated at the time point of input of the initial minimum value of thepulse wave corresponding to the pulse. That waveform address ADR1=A₀ iswritten to the peak information memory 525 (see FIG. 53). After this, oninput of the maximum value (address A₁) into the waveform samplingmemory 604, again a null cross detection signal Z is generated (see FIG.53). When the stroke between the maximum value and the immediatelypreceding minimum value (address A₀) is above a predetermined value, theaddress A₀ of the minimum value is written to the shift resistor (notshown in the figure) inside the micro-computer 606. The waveform addresswritten in this way, is then outputted from the shift resistor with adelay equivalent to two pulsations, and fetched to the micro-computer606 as the initial address of the waveform value WD of the one pulseportion to be transferred to the frequency analyzing unit 605. That isto say, in FIG. 52, on writing the address W_(n) of the maximum value ofthe pulse wave W_(N) corresponding to the certain pulsation, into theshift register, the starting address of the pulse wave W_(n−2) read intothe same shift resistor two pulses earlier (address of the first maximumvalue), is outputted from the shift register, and detected by themicro-computer 606.

At this time point, the micro-computer 606 refers to the contents of theshift register and obtains the difference amount, from the waveformaddress for the first minimum value of the pulse wave W_(n−2) until theaddress of the first minimum value of the next pulse wave W_(n−1). Thatis to say the number N of waveform values included in the pulse waveW_(n−1) of the single pulse portion is obtained. This is then outputtedtogether with the synchronizing signal SYNC to the frequency analyzingunit 605. Moreover, the internal connection conditions of thedistributor 721, selector 711 and 712, and selector 721 are changed, forexample to the solid line conditions in FIG. 51, by changing the selectsignal S12 which is synchronized with the synchronizing signal SYNC.

Subsequently, the micro-computer 606 successively increases the readaddress ADR4 from the waveform address of the first minimum value of thepulse wave W_(n−2), and supplies this to the waveform memory 503 by wayof the selector 512. Here the read address ADR4 is changed at a fasterspeed (for example two times the speed) than is the write address ADR1.This is so that all the waveform values corresponding to the pulse waveW_(n−2) which is prior to the pulse wave W_(n−1), can be read out beforethe maximum value of the pulse wave W_(n+1) of the pulse after the pulsewave W_(n) is input to the waveform sampling memory 604. In parallelwith the storage of the pulse wave W_(n) in the waveform memory 503, themicro-computer 606 reads the waveform value WD for the pulse waveW_(n−2) two pulses prior, from the waveform memory 503, and transfersthese values to the frequency analyzing unit 605, and successivelysupplies the values to the buffer memory 701 by way of the distributor721. The write address ADR5 is successively increased from “0” to “N−1”,synchronously while the waveform values WD are successively supplied tothe buffer memory 701, and these write addresses ADR5 are supplied tothe buffer memory 701 by way of the selector 711. As a result, therespective waveform values WD corresponding to the pulse wave W_(n−2),are stored in the respective storage areas for the addresses “0” to“N−1”, in the buffer memory 701.

(3) High Speed Playback

In parallel with the above operation, the high speed playback unit 730outputs the read addresses ADR6, and supplies these to the buffer memory702 by way of the selector 712.

As a result, the respective waveform values WD corresponding to thepulse wave W_(n−3) one pulse prior to the pulse wave W_(n−2) are readout from the buffer memory 702, and fetched to the high speed playbackunit 730 by way of the selector 722.

Here, the respective waveform values WD corresponding to the pulse waveW_(n−3) inside the buffer memory 702, are repeatedly read over aplurality of cycles at a higher speed than the speed at which therespective waveform values corresponding to the pulse wave W_(n−2) arestored in the buffer memory 701. At this time, the incrementing speed ofthe read address ADR6 is controlled so that the waveform values WD1corresponding to the pulse wave W_(n−3) are all read out within aspecified period T. That is to say, the high speed playback unit 730increments the read address ADR6 at a higher speed when the number ofwaveform values WD to be read from the buffer memory 702 has a large N1value as shown in FIG. 54. On the other hand, in the case of a small N2value as shown in FIG. 55, the read address ADR6 is incremented at aslower speed, so that the read address ADR6 changes the “0” to “N1-1” or“0” to “N2-1” segment within the specified period T. The waveform valueWD successively read out in this way is subject to an interpolationoperation in the high speed playback unit 730, and on attaining awaveform value WH of a specified sampling frequency m/T, is supplied tothe band pass filter 750.

(4) Spectrum Detector

The band pass filter 750 selects and passes a signal of frequency 1/Tfrom the time series data for the waveform WH, and supplies this to thespectrum detection unit 760. On the other hand, the sine wave generator740 generates a sine wave having a period T as shown in FIG. 56, andsupplies this to the spectrum detection unit 760. The spectrum detectionunit 760 detects the output signal level from the band pass filter 750over several waves, and outputs a representative value as the basic wavespectrum amplitude H₁ of the pulse wave W_(n−3). It also detects thephase difference between the output signal phase of the band pass filter750, and the output sine wave phase from the sine wave generator 740over several waves, and outputs the representative value as the basicwave spectrum phase q₁ for the pulse wave W_(n−3). From these respectiverepresentatives values, are calculated for example the output signallevel corresponding to the respective waves immediately before output ofthe basic wave spectrum, and the mean movement value of the phasedifference.

Next, the high speed playback unit 730 sets the incrementing speed ofthe read address ADR6 to ½ in the case of basic wave spectrum detection,so as to read all of the waveform values for the pulse wave W_(n−3)within the specified period 2T. It also repeatedly reads out thewaveform values WH corresponding to the pulse wave W_(n−3), and suppliesthese to the band pass filter 750 (see FIG. 56). Then a signal offrequency 1/T, in the time scale data constituting the waveform valueWH, that is to say the signal corresponding to the second harmonic ofthe pulse wave W_(n−3), is passed by the band pass filter 750, andsupplied to the spectrum detection unit 760. As a result the amplitudeH₂ of the second harmonic spectrum of the pulse wave W_(n−3), isdetected by the spectrum detection unit 760, and is outputted.

On the other hand, the sine wave generator 740 generates a sine wavehaving a period 2T, and supplies this to the spectrum detection unit 760(see FIG. 56). As a result, the phase q₂ of the basic wave spectrum ofthe pulse wave W_(n−3) is outputted by the spectrum detection unit 760.

After this, in the case of the basic wave spectrum, the increment speedof the read address ADR6 is successively changed as {fraction (1/3+L )},{fraction (1/4+L )}, {fraction (1/5+L )}, {fraction (1/6+L )}. Theperiod of the sine wave generated by the sine wave generator 740 is alsosuccessively changed in conformity as 3T, 4T, 5T, 6T, and an operationsimilar to the above carried out. The amplitudes H₃ to H₆ and phases q₃to q₆ of the 3rd to 6th harmonic spectrums, are output from the spectrumdetection section 760. The respective spectrums for the pulse waveW_(n−3) obtained in this way are fetched by the micro-computer 606.

The micro-computer 606 then computes the frequency:$f = \frac{1}{N \cdot \tau}$

of the basic wave, using the number N of waveform values WDcorresponding to the pulse wave W_(n−3) and the period τ of the clock φ,and outputs this together with the above-mentioned spectrum, from theoutput section 603.

Subsequently, the pulse wave W_(n+1) one pulsation after the pulse waveW_(n), rises, and on input of the initial maximum value into thewaveform sampling memory 604, the micro-computer 606 generates asynchronized signal SYNC and outputs the number N of the waveform valuesWD included in the pulse wave W_(n−2). Furthermore, the select signalS12 is inverted so that the internal connection conditions in thedistributor 721, selectors 711 and 712, and selector 721 become thoseshown by the broken line in FIG. 51. Moreover, in parallel with storageof the pulse wave W_(n+1) in the waveform memory 503, the micro-computer606 reads from the waveform memory 503, the waveform values WD for thepulse wave W_(n−1) two pulses prior, and transfers these to thefrequency analyzing unit 605, and successively supplies them to thebuffer memory 702 by way of the distributor 721. On the other hand, inparallel with this operation, the high speed playback unit 730 readsfrom the buffer memory 701, the respective waveform values WDcorresponding to the pulse wave W_(n−2) one pulsation prior to the pulsewave W_(n−1), and then outputs these as waveform values WH afterinterpolation by the high speed playback unit 730. A similar processingto that for pulse wave W_(n−3), is then carried out on the waveformvalues WH corresponding to the pulse wave W_(n−2), and the spectrumobtained.

Subsequently, the successively arriving respective pulse waves areprocessed in a similar manner to the above, and the spectrums for therespective pulse waves are obtained in succession and are outputted fromthe output unit 603, as waveform parameters corresponding to theindividual pulses.

CHAPTER 5-2 Pulse Wave Analyzer (ii)

In the analyzer (i) explained in Chapter 5-1, the waveform data storedin the waveform memory 503, was played backed as pulsations and thepulse wave spectrum computed for each pulsation. In contrast to this,with the present analyzer (ii), a technique is used such as thatproposed by the present inventor in Chapter 2. With this technique, thevalues for respective elements of the electrical model, modeled on thearterial system dynamics of an examinee, are obtained on the basis ofthe pulse waves obtained from the examinee, and the results used ascondition indicating parameters.

The Model considers four parameters of the factors deciding the behaviorof the human circulatory arterial system; namely the moment due to theblood flow in the arterial system proximal section, the vascularresistance due to the blood viscosity in the proximal section, thecompliance of the blood vessels (viscous elasticity) at the proximalsection, and the vascular resistance at the distal section, and modelsthese four parameters as an electrical model. The details of the modelhave described in Chapter 2-1.

In the present analyzer (ii), the micro-computer 606 by way of theselector 722, successively writes to one of the buffer memories 701,702, the waveform data corresponding to the respective pulses, and readsfrom the other buffer memory which is not being written to, waveformdata corresponding to one pulse. It then simulates the operation of thefour parameter model at the time an electrical signal corresponding tothe pressure wave at the arterial beginning section is applied thereto,estimates the values for the various parameters of the electrical modelso as to output waveforms corresponding to the waveform data read fromthe buffer memory 701 or 702, and outputs the calculated results aswaveform parameters. The values for the various parameters in theelectrical model can be obtained through trial and error by changing thevalues for the parameters and repeating the simulation operation.However it is also possible to use the technique described in Chapter 2.Moreover, the dynamic circulatory parameters may be obtained from thedistortion of the pulse waveform described in Chapter 3.

CHAPTER 5-3 Variation of the Fifth Embodiment

The fifth embodiment is not limited to the above analyzers (i) and (ii).For example, a number of variations such as given below are alsopossible.

Analyzer (iii)

In the above analyzer (i) described in Chapter 5-1, the frequencyanalysis of the pulse wave was carried out by hardware. However thepresent embodiment is not limited to this, and frequency analysis may becarried out with software executed by the micro-computer 606.Furthermore frequency analysis methods such as DFT (Discrete FourierTransform), FFT (Fast Fourier Transform) and the like may be suitable.

Analyzer (iv)

In the above respective Analyzers (i) and (ii) described in Chapter 5-1and 5-2, the waveform parameters corresponding to the respectivepulsations were outputted in real time as they were each obtained.However the output method for the waveform parameters is not limited tothis method. For example the micro-computer 606 can compute the mean sumvalue of the waveform parameters for a predetermined number ofpulsations and output this. Moreover, the micro-computer 606 cancalculate the mean sum value of the waveform parameters of thepredetermined number of previous pulsations, that is to say, the meanmovement value of the waveform parameters, and output this in real time.

Analyzer (v)

In Chapter 5-1 and 5-2, the above respective analyzers (i) and (ii) forcarrying out analysis of the radial pulse has been described. Howeverthe object of analysis of the present invention is not limited to onlythe radial pulse. For example it may also be applicable to fingertippulse waves etc. and other types of pulse waves.

Analyzer (vi)

Many parameters apart from those given in the respective examples can beconsidered as waveform parameters of the pulse wave. When the pulse waveanalyzer according to the present invention is used for diagnosis, thewaveform parameters can be changed to obtain those suitable for thediagnosis. For example, in Chapter 4, the present inventor proposed anapparatus for obtaining an examinee's stress level based on theamplitude and phase of the peak points appearing in the pulse wave. Withthe apparatus according to the above embodiment, information related tothe peak points can be obtained from the pulse waves corresponding toeach pulse, and used for evaluation of stress levels.

In the present invention, the living body refers to the body of theexaminee to be subjected to diagnosis or analysis, but the living bodyis not necessarily limited only to a human body. The basic principleoutlined in the present invention should be equally applicable to animalbodies.

Furthermore, the present invention is not limited by the embodimentspresented in Chapter 1 to Chapter 5. Various other modifications orapplications are possible within the principle of diagnosis based ondetailed analyses of pulse waveforms.

While the invention has been described in conjunction with severalspecific embodiments, it is evident to those skilled in the art thatmany further alternatives, modifications and variations will be apparentin light of the foregoing description. Thus, the invention describedherein is intended to embrace all such alternatives, modifications,applications and variations as may fall within the spirit and scope ofthe appended claims.

What is claimed is:
 1. A pulse wave analyzing apparatus, comprising:pulse wave inputting means for inputting information representing aradial arterial pulse wave of a living body; and analyzing means for (1)creating a waveform model of a blood pressure waveform at a proximalsection of the living body; (2) utilizing an electrical model simulatingan arterial system from the proximal section to the distal portion of aliving body, (3) computing values of elements of said electrical modelso that an output waveform similar to said radial arterial pulsewaveform is output from the electrical model in response to input ofsaid waveform model; and (4) outputting the computed values ascirculatory dynamic parameters.
 2. The pulse wave analyzing apparatus ofclaim 1 wherein said analyzing means creates said waveform model basedon an actual blood pressure waveform obtained from a section of saidliving body other than said proximal section.
 3. The pulse waveanalyzing apparatus of claim 1, wherein said waveform model is atriangular waveform simulating said blood pressure waveform.
 4. Thepulse wave analyzing apparatus of claim 1, wherein said waveform modelis a step-and-ramp waveform simulating said blood pressure waveform. 5.The pulse wave analyzing apparatus of claim 1, wherein the circulatorydynamic parameters from said analyzing means are written to a storagemedia.
 6. The pulse wave analyzing apparatus of claim 1, where saidpulse wave inputting means inputs said information continuously over aperiod of time.
 7. The pulse wave analyzing apparatus of claim 1,wherein said electrical model is a four parameter model comprising: (i)a first resistor simulating vascular resistance due to blood flowviscosity in said proximal section of said arterial system; (ii) aninductor simulating blood flow momentum in said proximal section of saidarterial system; (iii) a capacitor simulating vascular elasticity insaid proximal section of said arterial system; and (iv) a secondresistor simulating vascular resistance due to blood flow viscosity insaid distal section of said electrical circuit; and wherein a seriescircuit with said first resistor and said inductor in series, and aparallel circuit with said capacitor and said second resistor inparallel, are successively arranged in series between a pair of inputterminals of said four parameter model.
 8. The pulse wave analyzingapparatus of claim 7, wherein the apparatus further comprises means formeasuring a stroke volume of the living body and said analyzing meansfurther includes means for estimating a value of said inductance basedon the stroke volume.
 9. The pulse wave analyzing apparatus of claim 7,wherein the apparatus further comprises means for measuring a blood flowrate of the living body and said analyzing means further includes meansfor estimating a value of said inductance based on the blood flow rate.10. A diagnostic apparatus, comprising: analyzing means for creatingwaveform parameters from information representing a pulse wave of aliving body; and diagnostic means for performing a diagnosis of acondition of said living body on the basis of said waveform parameters;and wherein said analyzing means is for (1) creating a waveform model ofa blood pressure waveform at a proximal section of the living body; (2)utilizing an electrical model simulating an arterial system from theproximal section to the distal portion of a living body, (3) computingvalues of elements of said electrical model so that an output waveformsimilar to said radial arterial pulse waveform is output from theelectrical model in response to input of said waveform model; and (4)outputting the computed values as waveform parameters.
 11. Thediagnostic apparatus of claim 10, wherein said electrical model is afour parameter model comprising: (i) a first resistor simulatingvascular resistance due to blood flow viscosity in said proximal sectionof said arterial system; (ii) an inductor simulating blood flow momentumin said proximal section of said arterial system; (iii) a capacitorsimulating vascular elasticity in said proximal section of said arterialsystem; and (iv) a second resistor simulating vascular resistance due toblood flow viscosity in said distal section of said electrical circuit;and wherein a series circuit with said first resistor and said inductorin series, and a parallel circuit with said capacitor and said secondresistor in parallel, are successively arranged in series between a pairof input terminals of said four parameter model.